{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Loading environment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "%pylab inline\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.pyplot import show\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import subprocess as sp\n",
    "import os"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Import of files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.DataFrame([])\n",
    "\n",
    "### Rosetta score file\n",
    "\n",
    "outscore=r\"./out/score.sc\"\n",
    "if (os.path.exists(outscore)):\n",
    "    columns_to_keep = ['ddg_pre','ddg_post','nddg_pre','nddg_post','hbonds_pre','hbonds_post', 'bunsh_pre','bunsh_post',\n",
    "    'bunsh2_pre','bunsh2_post', 'sc_pre','sc_post', 'sasa_pre','sasa_post', 'cms_pre','cms_post', 'description']\n",
    "    df = pd.read_csv(outscore, sep='\\s+', skiprows=1)\n",
    "    df = df[df.total_score != 'total_score'].drop(columns=[col for col in df.columns if col not in columns_to_keep])\n",
    "    df = df.applymap(lambda x : pd.to_numeric(x,errors='ignore'))\n",
    "\n",
    "    df1=pd.DataFrame([])\n",
    "    dico_seedname={}\n",
    "\n",
    "    for idx in df.index:\n",
    "        description=df.loc[idx,'description']\n",
    "        splited_description=df.loc[idx,'description'].split('_')\n",
    "        seed=splited_description[2] +'_'+splited_description[3] +'_'+splited_description[4]\n",
    "        dico_seedname[description]=seed\n",
    "        \n",
    "    df['seed'] = df['description'].map(dico_seedname)\n",
    "    df['nddg_pre']=df['ddg_pre']/df['sasa_pre']*1000\n",
    "    df['nddg_post']=df['ddg_post']/df['sasa_post']*1000\n",
    "\n",
    "### Similarity score    \n",
    "    \n",
    "outsimi='./similarity.csv'\n",
    "dico_unique={}\n",
    "dico_cn={}\n",
    "if (os.path.exists(outsimi)):\n",
    "    df2 = pd.read_csv(outsimi, sep=',').dropna()\n",
    "    for idx in df2.index:\n",
    "        name=df2.loc[idx,'design']\n",
    "        uniqueness=df2.loc[idx,'similarity']\n",
    "        closest_neighboor=df2.loc[idx,'best_match']\n",
    "        dico_unique[name]=uniqueness\n",
    "        dico_cn[name]=closest_neighboor\n",
    "    df['similarity'] = df['description'].map(dico_unique)\n",
    "    df['closest_neighboor'] = df['description'].map(dico_cn)\n",
    "\n",
    "### Contacts to molecule\n",
    "\n",
    "outcontacts='contacts.csv'\n",
    "dico_contacts={}\n",
    "if (os.path.exists(outcontacts)):\n",
    "    df3 = pd.read_csv(outcontacts, sep=',').dropna()\n",
    "    for idx in df3.index:\n",
    "        name=df3.loc[idx,'design']\n",
    "        contacts=df3.loc[idx,'mol_contacts']\n",
    "        dico_contacts[name]=contacts\n",
    "    df['mol_contacts'] = df['description'].map(dico_contacts)\n",
    "\n",
    "### DSSP ratio (Beta sheet-seed only)\n",
    "\n",
    "outdssp='dssp.csv'\n",
    "dico_dssp={}\n",
    "if (os.path.exists(outdssp)):\n",
    "    df4 = pd.read_csv(outdssp, sep=',').dropna()\n",
    "    for idx in df4.index:\n",
    "        name=df4.loc[idx,'design']\n",
    "        ratio=df4.loc[idx,'ratio']*100\n",
    "        dico_dssp[name]=ratio\n",
    "    df['dssp_ratio'] = df['description'].map(dico_dssp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bunsh2_post</th>\n",
       "      <th>bunsh2_pre</th>\n",
       "      <th>bunsh_post</th>\n",
       "      <th>bunsh_pre</th>\n",
       "      <th>cms_post</th>\n",
       "      <th>cms_pre</th>\n",
       "      <th>ddg_post</th>\n",
       "      <th>ddg_pre</th>\n",
       "      <th>hbonds_post</th>\n",
       "      <th>hbonds_pre</th>\n",
       "      <th>...</th>\n",
       "      <th>sasa_pre</th>\n",
       "      <th>sc_post</th>\n",
       "      <th>sc_pre</th>\n",
       "      <th>description</th>\n",
       "      <th>seed</th>\n",
       "      <th>nddg_pre</th>\n",
       "      <th>nddg_post</th>\n",
       "      <th>similarity</th>\n",
       "      <th>closest_neighboor</th>\n",
       "      <th>mol_contacts</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>120.812</td>\n",
       "      <td>120.431</td>\n",
       "      <td>-10.364</td>\n",
       "      <td>-10.571</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>779.036</td>\n",
       "      <td>0.523</td>\n",
       "      <td>0.565</td>\n",
       "      <td>6O0K_A_102520-1fw9_A_2</td>\n",
       "      <td>102520-1fw9_A_2</td>\n",
       "      <td>-13.569334</td>\n",
       "      <td>-13.206518</td>\n",
       "      <td>0.166667</td>\n",
       "      <td>6O0K_A_102225-3r6f_A_9</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>159.773</td>\n",
       "      <td>166.738</td>\n",
       "      <td>-17.519</td>\n",
       "      <td>-16.702</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1003.671</td>\n",
       "      <td>0.668</td>\n",
       "      <td>0.663</td>\n",
       "      <td>6O0K_A_104007-1yj5_C_0</td>\n",
       "      <td>104007-1yj5_C_0</td>\n",
       "      <td>-16.640911</td>\n",
       "      <td>-18.257650</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>6O0K_A_104427-1stz_A_0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>132.160</td>\n",
       "      <td>128.324</td>\n",
       "      <td>-10.734</td>\n",
       "      <td>-8.957</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>...</td>\n",
       "      <td>770.544</td>\n",
       "      <td>0.506</td>\n",
       "      <td>0.671</td>\n",
       "      <td>6O0K_A_100210-1pfz_A_0</td>\n",
       "      <td>100210-1pfz_A_0</td>\n",
       "      <td>-11.624255</td>\n",
       "      <td>-13.293241</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>6O0K_A_104427-1stz_A_0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>130.515</td>\n",
       "      <td>134.496</td>\n",
       "      <td>-11.824</td>\n",
       "      <td>-11.298</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>...</td>\n",
       "      <td>836.058</td>\n",
       "      <td>0.575</td>\n",
       "      <td>0.605</td>\n",
       "      <td>6O0K_A_100101-3s2k_A_1</td>\n",
       "      <td>100101-3s2k_A_1</td>\n",
       "      <td>-13.513417</td>\n",
       "      <td>-14.240739</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>6O0K_A_101921-2vsd_A_1</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>99.435</td>\n",
       "      <td>98.777</td>\n",
       "      <td>-14.583</td>\n",
       "      <td>-13.639</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>...</td>\n",
       "      <td>911.758</td>\n",
       "      <td>0.439</td>\n",
       "      <td>0.460</td>\n",
       "      <td>6O0K_A_100882-2e6x_A_3</td>\n",
       "      <td>100882-2e6x_A_3</td>\n",
       "      <td>-14.959013</td>\n",
       "      <td>-16.184883</td>\n",
       "      <td>0.428571</td>\n",
       "      <td>6O0K_A_102225-3r6f_A_3</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   bunsh2_post  bunsh2_pre  bunsh_post  bunsh_pre  cms_post  cms_pre  \\\n",
       "0          1.0         0.0         0.0        1.0   120.812  120.431   \n",
       "1          4.0         5.0         3.0        4.0   159.773  166.738   \n",
       "2          4.0         3.0         4.0        2.0   132.160  128.324   \n",
       "3          5.0         4.0         1.0        1.0   130.515  134.496   \n",
       "4          4.0         4.0         3.0        3.0    99.435   98.777   \n",
       "\n",
       "   ddg_post  ddg_pre  hbonds_post  hbonds_pre  ...  sasa_pre  sc_post  sc_pre  \\\n",
       "0   -10.364  -10.571          0.0         0.0  ...   779.036    0.523   0.565   \n",
       "1   -17.519  -16.702          2.0         2.0  ...  1003.671    0.668   0.663   \n",
       "2   -10.734   -8.957          4.0         4.0  ...   770.544    0.506   0.671   \n",
       "3   -11.824  -11.298          4.0         4.0  ...   836.058    0.575   0.605   \n",
       "4   -14.583  -13.639          4.0         4.0  ...   911.758    0.439   0.460   \n",
       "\n",
       "              description             seed   nddg_pre  nddg_post  similarity  \\\n",
       "0  6O0K_A_102520-1fw9_A_2  102520-1fw9_A_2 -13.569334 -13.206518    0.166667   \n",
       "1  6O0K_A_104007-1yj5_C_0  104007-1yj5_C_0 -16.640911 -18.257650    0.500000   \n",
       "2  6O0K_A_100210-1pfz_A_0  100210-1pfz_A_0 -11.624255 -13.293241    0.500000   \n",
       "3  6O0K_A_100101-3s2k_A_1  100101-3s2k_A_1 -13.513417 -14.240739    0.400000   \n",
       "4  6O0K_A_100882-2e6x_A_3  100882-2e6x_A_3 -14.959013 -16.184883    0.428571   \n",
       "\n",
       "        closest_neighboor mol_contacts  \n",
       "0  6O0K_A_102225-3r6f_A_9           15  \n",
       "1  6O0K_A_104427-1stz_A_0            4  \n",
       "2  6O0K_A_104427-1stz_A_0            6  \n",
       "3  6O0K_A_101921-2vsd_A_1            9  \n",
       "4  6O0K_A_102225-3r6f_A_3           18  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Metrics analysis\n",
    "This section analyzes the improvement of each Rosetta metrics after design compared to the metrics prior design."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#You can add other metrics there, as long as there is a '_pre' and '_post' suffix\n",
    "metrics = [['ddg_pre','ddg_post'],['nddg_pre','nddg_post'],['hbonds_pre','hbonds_post'], \n",
    "           ['bunsh_pre','bunsh_post'],['bunsh2_pre','bunsh2_post'], ['sc_pre','sc_post'], ['sasa_pre','sasa_post'],\n",
    "          ['cms_pre','cms_post']]\n",
    "\n",
    "# Don't touch this part\n",
    "pre_data = pd.DataFrame([])\n",
    "post_data = pd.DataFrame([])\n",
    "comparison = pd.DataFrame([])\n",
    "\n",
    "for metric in metrics:\n",
    "    for element in metric:\n",
    "        name = element.split('_')\n",
    "        if name[1] == 'pre':\n",
    "            pre_data[name[0]] = df.loc[:,element]\n",
    "        elif name[1] == 'post':\n",
    "            post_data[name[0]] = df.loc[:,element]\n",
    "            comparison[name[0]] = (post_data[name[0]]>pre_data[name[0]])\n",
    "\n",
    "pre_data[\"Data\"] = \"Pre-design\"\n",
    "post_data[\"Data\"] = \"Post-design\"\n",
    "all_data = pd.concat([pre_data, post_data])           "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_plot(all_data, metric, boxlabel_x, boxlabel_y, scattlabel_x, scattlabel_y):\n",
    "    #Boxplot\n",
    "    fig, axs = plt.subplots(1, 2, figsize=(15, 4))\n",
    "    plt.subplots_adjust(wspace=0.5)\n",
    "    g1 = sns.boxplot(x=\"Data\", y=metric, hue=\"Data\", data=all_data, showfliers = False, ax=axs[0])\n",
    "    axs[0].set_xlabel(boxlabel_x)\n",
    "    axs[0].set_ylabel(boxlabel_y)\n",
    "\n",
    "    #Scatterplot\n",
    "    g2 = sns.scatterplot(x=df['{}_pre'.format(metric)],y=df['{}_post'.format(metric)], hue=comparison[metric],legend = False, ax=axs[1])\n",
    "    axis=[g2.get_xlim(), g2.get_ylim()]\n",
    "    g2.set_xlim(left=min(min(axis)), right=max(max(axis)))\n",
    "    g2.set_ylim(bottom=min(min(axis)), top=max(max(axis)))\n",
    "    x0, y0 = g2.get_xlim()\n",
    "    x1, y1 = g2.get_ylim()\n",
    "    axs[1].set_xlabel(scattlabel_x)\n",
    "    axs[1].set_ylabel(scattlabel_y)\n",
    "    axs[1].plot([x0, y0], [x1, y1], 'k--')\n",
    "\n",
    "    # Statistics\n",
    "    pre_medi=pre_data[metric].median()\n",
    "    post_medi=post_data[metric].median()\n",
    "    print(f\"Median pre-design: {pre_medi:.2f} / Median post-design: {post_medi:.2f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Computer binding energy (ddG)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Median pre-design: -15.96 / Median post-design: -16.93\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA30AAAEGCAYAAADR8PySAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuNSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/xnp5ZAAAACXBIWXMAAAsTAAALEwEAmpwYAABNFUlEQVR4nO3dd3gVZfrG8e9D6L2JCEi1sgqWiF0Ry7o/BRUsa12liaAgFlQsYEFRiroqu7LYcG0rimAFwUUQbFQRsLA2UFSKSA8pz++PM9FjSE5OknMyJ8n9ua5cOTNzZuYGTjI8877zvubuiIiIiIiISPlUKewAIiIiIiIikjwq+kRERERERMoxFX0iIiIiIiLlmIo+ERERERGRckxFn4iIiIiISDlWOewAidC4cWNv3bp12DFERMqUBQsWrHP33cLOIZIfXdtFROKzZcsWVq5cSXZ2doHX9XJR9LVu3Zr58+eHHUNEpEwxs2/DziBSEF3bRURic3fMjPXr13PZZZfx6quvFnhdT7nunWZ2kJl9YGaLzWy+mXUKO5OIiIgUj67rIiKJlZOTw6OPPspJJ51EVlYWjRo1YurUqTH3SbmiD7gPuN3dDwJuC5ZFRESkbNJ1XUQkQb788ku6dOlCv379ANi4cWNc+6Vi0edA3eB1PeCHELOIiIhIyei6LiJSQllZWYwePZoOHTqwePFiJkyYwIwZM2jcuHFc+5u7Jzli0ZjZ/sA0wIgUpUe5+y79U82sL9AXoGXLlod++60eTRERKQozW+Du6WHnkPIt3ut68F5d20VE8pGRkcFBBx3Evvvuy7hx42jWrNku74l1XQ+l6DOzGUDTfDbdDJwIvOvuL5nZuUBfdz8p1vHS09NdD3uLiBSNij5JlERf10HXdhGRjIwMHnjgAfr370+dOnVYv349DRs2xMzyfX+s63ooo3fG+mVvZhOBQcHii8CEUgklIiIixaLruohIYn3wwQf06tWL5cuXs8cee3DJJZfQqFGjYh8vFZ/p+wE4PnjdBfgyxCwiIiJSMrqui4jEaevWrQwePJijjjqKzZs388Ybb3DJJZeU+LipOE9fH+BBM6sM7CDo2y8iIiJlkq7rIiJx6t+/PxMnTmTAgAHcc8891KlTJyHHLbDoM7Pucey/w93fSEiSgLu/BxyayGOWJZ07dw47QkqZNWtW2BFERKQEKvp1XUSkMBs3biQjI4Pdd9+dYcOG0bt3b4499tiEniNWS9+/gClERtsqyHFAQou+ii4VipzOnTunRA4RERERkfLslVdeoX///hx++OFMnjyZtm3b0rZt24SfJ1bR96a794y1s5n9O8F5REREREREyrWffvqJq666ihdffJGOHTtyyy23APDL1p1Ur5JGjappCT1fgUWfu19U2M7xvEdEREREREQi3nvvPc444wy2bNnCiBEjuP7661m7NYtH/vslz3+8ilYNazLoxH1Ib92gwOkZiqpYo3eaWX5z8YiIiIiIiEg+cudHb9++PcceeyyLFy9m6NChVEqrzJPzvmHUtC9YtWE7761cz0WPfciKNZsSdu7iTtnwWMISiIiIiIiIlFM5OTk88sgjnHDCCWRlZdGwYUNeeeUV9t9/fwB+/HU7T8375g/7ZGTl8PmPmxOWoVhTNrj7aQlLICJlgkaW/SMNdiQiIiKF+fzzz+nduzfvvfceJ598Mr/++usuk6xXqVyJutWrsHZLxh/WV6+SuOf6Yk3Z0DDPKgc2em67pIhUKKlQ5GhkWRERESkLsrKyGDNmDMOGDaNGjRo88cQT/O1vf8v3Gb0mdaoz9LT9GPzCkt/WtW5UkwOa10tYnlgtfQuIFHrRyWqb2RKgt7t/k7AUIiIiIiIi5UR2djYTJ07ktNNO45FHHqFp09hDopzSvinP9qnO/G9+oWnd6hzWpgF7NqyZsDyxRu9sk9/6YNL2fwKnJiyFiIiIiIhIGbZjxw7uv/9+rrzySurUqcN7771HgwYN4tq3VrXKHNWuMUe1a5yUbEUeyMXdXwaaJCGLiIiIiIhImTNv3jwOPvhghg4dyiuvvAIQd8FXGopc9JlZ7eLsJyIiIiIiUp5s2bKFgQMHcswxx7Bt2zbeeustLr744rBj7SLWQC7X5LO6AdANeDhpiURERERERMqAAQMG8PTTTzNgwADuvvtu6tSpE3akfMUayCVvYgd+BC5y96XJiyQiIiIiIpKaNmzYwM6dO2natCnDhg2jT58+HHPMMWHHiinWQC63l2YQERERERGRVPbSSy8xYMAAjjjiCF555RXatm1L27Ztw45VqGI9m2dmfRMdREREREREJBWtWbOGHj16cPbZZ9OsWTOGDx8edqQiidW9M5ZdZxUUEREREREpZ+bMmUO3bt3Yvn07I0eO5JprrqFKlSphxyqSYrX0ufujJTmpmZ1jZsvMLMfM0vNsu8nMVprZ52b255KcR0REREqHru0iUt64OwAHHHAAXbp0YcmSJdxwww1lruCDGEWfmT0Q9XpQnm1PlvC8nwLdgdl5jtse+CvwJyKTv48zs7QSnktERESST9d2ESkXcnJyeOihh+jcuTNZWVk0aNCAl156iX333TfsaMUWq6XvuKjXf8uzrUNJTuruK9z983w2nQE87+4Z7v41sBLoVJJziYiISPLp2i4i5cFnn33Gcccdx8CBA6lZsyabNm0KO1JCxCr6rIDXydQcWBW1vDpYtwsz62tm881s/tq1a0slnIiIiBSZru0ikvIyMzO5++676dixIytWrGDixIm88cYbNGzYMOxoCRFrIJdKZtaASGGY+zq3+Cu0W4aZzQCa5rPpZnefUuSkebj7eGA8QHp6upf0eCIiIhKbru0iUiZtXAU/Lwd32L091G+5y1tycnJ45plnOOOMM3jooYfYfffdQwiaPLGKvnrAAn4v9BZGbSv0F7G7n1SMPN8De0YttwjWiYiISMh0bReRMufnz+DZc2Hjt5HlenvChZOgyX5s376dMWPGMHDgQOrWrcvcuXOpX79+qHGTJdbk7K1LMUeuqcCzZjYWaAbsDXwUQg4RERFJDF3bRSQ8yyb/XvAB/LoKPn2JOVWOo3fv3nzxxRe0bt2aiy66qNwWfFDMKRtKyszOMrPVwJHA62Y2DcDdlwH/AZYDbwED3D07jIwiIiISP13bRSQlrf74D4ubM5wBIyZw3HHHsXPnTt5++20uuuiikMKVnmIVfWa2qCQndffJ7t7C3au5++7u/ueobSPcvZ277+vub5bkPCIiIlI6dG0XkZR0QPc/LA54Ywf/+O+3XH311Xz66aecdFJxeq0Xjbv/NudfWGI901cgdz840UFEREREREQSqt1JrN//MjLnP0XTOsbtV19G/5ZdOeLE05N+6p1ZOSz4dgMT3/+WnVk5/O2o1hzWpgE1qhSrBCuRIp/RzE4Ghrj7yUnIIyIiIiIiUmLuzqRpc7hy4HMceWg6r0wcR5v6rWlTuUqpnH/Rd79wwYQPyW3km/nZzzx12WEcv2+TUjl/tAK7d5pZFzP7wsy2mNm/zexAM5sPjAT+UXoRRURERERE4rdmzRq6d+/Oueeey5577snt94yGxntDKRV8AFOW/EDeXp1PzPuGnJzS7+oZq6VvDNAXeB/4S/D9Rnd/uDSCiYiIiIiIFNXs2bPp1q0bGRkZ3HfffQwePJjKlUPoUlnJdllXpVIo42jGHMjF3X2Wu2e4+yvA9yr4REREREQkFeUOlnLggQdy8skns2TJEq6//vpQCj6Abh2bkRZV+JnBpUe3plI+xWCyxfobqG9m0cPdVI5edveXkxdLRERERESkcNnZ2Tz00EO89NJLvPPOOzRo0IAXX3wx7Fgc3LIB/+l7BK8s/p7MbOfMg5pzSKv6oWSJVfS9C3SNWp4dteyAij4REREREQnN8uXL6dWrFx988AGnnXYamzdvpmHDhmHHAiCtknFo64Yc2jr8PAUWfe5+WWkGERERERERiUdmZiYjR47krrvuok6dOjzzzDOcf/75mJV+18myINbonYVOXhHPe0RERERERBLJ3fnPf/5D9+7dWbFiBRdccIEKvhhide8cZWbfA7H+9u4GXktsJBERERERkT/atm0bo0eP5uqrr6Zu3brMnTuXunXrhh2rTIhV9P0EjC1k/y8TmEVERERERGQX7777Lr1792blypW0a9eOCy+8UAVfEcR6pq9zKeYQERERERH5g02bNnHDDTfwz3/+k7Zt2zJz5ky6dOkSdqwyJ5zZAUVERERERApx5ZVXMn78eK655hqWLl2qgq+YwpmpUEREREREJB/r1q0jMzOTPfbYgzvuuIMBAwZw+OGHs31nFp+t2YTjtGxUi1pVVcrES39TIiIiFYCZXRPH27a6+6NJDyMikg9354UXXuCqq67iqKOOYsqUKbRu3ZrWrVuz5tftjJ3+BZMWrsYd/u/Apgz9v/1p0aBm2LHLhEK7d5pZEzM7y8wGmFlPM+tkZuoWKiIiUrZcD9QG6sT4uja0dCJSoX3//fecccYZnH/++bRt25YRI0b8YfucL9fx4oJIwQfwxtIfmb7spxCSlk0FtvSZ2QnAjUBDYBHwM1AdOBNoZ2aTgDHuvqmoJzWzc4DhwP5AJ3efH6w/GRgJVAV2Ate7+ztFPb6IiIjs4ml3vyPWG8ysVnEPrmu7iBTXu+++S7du3cjMzGTMmDEMGjSItLS0P7znnRW7FnhvLF3DpUe1plIlzc9XmFjdO/8P6OPu3+XdYGaVgdOBk4GXinHeT4HuQN4uJOuAru7+g5kdAEwDmhfj+CIiIhLF3Yck4j0x6NouIkWSk5NDpUqV6NixI3/5y18YMWIE7dq1y/e96a0b8laelr2j9mqkgi9OBXbTdPfr8yv4gm1Z7v6Kuxen4MPdV7j75/msX+TuPwSLy4AaZlatOOcQERGR+JjZISU9hq7tIhKv7Oxsxo4dyzHHHENmZib169fn+eefL7DgAzhx/yb8aY/f5+Vr17gW3Trq/lG8YnXvbAG0dvf3guVriDwLAPCsu69McrYewEJ3zyggX1+gL0DLli2THEVERKRcuwLoUwrn0bVdpIL79NNP6dWrFx999BGnn346W7ZsoUGDBoXu16ZxbZ7oeRgrf95CTo6zd5M67F6veikkLh9ide8cBTwTtXw5MB6oCdwOXBjrwGY2A2iaz6ab3X1KIfv+CbgXOKWg97j7+CAP6enpHut48Tirx9n8sn5dSQ9TbnTu3DnsCCmhQaPGTH5pUtgxRESSyt3jKvjK2rVdRFLHzp07ueeeexgxYgT16tXjueee47zzzsMs/u6ZTepUp0kdFXrFEavo29fdX4ta3ubuYwDMbE5hB3b3k4oTKGhhnAxc4u7/K84xiuOX9evYfFjP0jqdlBUfPx52AhGRhMinC6cD69x9VbzHKGvXdhFJLZMmTeLcc8/lgQceoHHjxmHHqVBiFX15y+gTo14n5V/JzOoDrwM3uvvcZJxDRESkghqTz7qGZlYVON/dFyfjpLq2i1RcW7du5b777uOaa66hXr16zJs3jzp16oQdq0KKNd/eZjPbJ3fB3TcAmNl+wOaSnDSY9281cCTwuplNCzZdCewF3GZmi4OvJiU5l4iIiIC7n5DPV0fgYuDvJT2+ru0iEu2dd96hQ4cO3HHHHbzxxhsAKvhCFKulbxjwmpmNABYG6w4FhgKDSnJSd59MpJtH3vV3AXeV5NgiIiISP3efb2a1C39nocfRtV1E2LhxI9dffz0TJkxgr732YtasWRx//PFhx6rwCiz63P0tM+sODAEGBquXAd3d/dPSCCciIiLJZWa7E3m+T0SkxK666iqeffZZhgwZwvDhw6lRo0bYkYTYLX0Exd0lpZRFREREksTMHmLX4q4hcBQl7MEjIhXbzz//TFZWFs2aNePOO+9k0KBBpKenhx1LosSap+9VYtz5c/duSUkkIiIiyTA/z7ID64Fr3P3nEPKISBnn7jz77LMMGjSIo48+milTptC6dWtat24ddjTJI1ZL3+jge3cic/L8O1g+H/gpmaFEREQksdz9qbAziEj5sWrVKq644gpef/11jjjiCO65556wI0kMsZ7pexfAzMa4e3T77KtmlvduoYiIiJRRZjbc3YeHnUNEyoZ3332Xrl27kp2dzQMPPMCVV15JWlpa2LEkhlhTNuSqZWZtcxfMrA1QK3mRREREpJQtCDuAiKS+nJwcADp27Mjpp5/O0qVLGTRokAq+MiDmQC6BwcAsM/sKMKAVcHlSU4mIiEipcfdXw84gIqkrKyuLsWPHMnnyZGbPnk39+vV59tlnw44lRVBoS5+7vwXsTWRkr4HAvu4+LfZeIiIikkrM7D9Rr+/Ns2166ScSkbJgyZIlHHHEEdxwww00bdqULVu2hB1JiiHW6J3dC9jUzsxw95eTlElEREQSb++o1ycDN0Qt71bKWUQkxe3cuZM777yTkSNH0rBhQ1588UV69OiBmYUdTYohVvfOrsH3JkTm8JlJpHvnCcA8QEWfSCk4t8dZ/Lz+l7BjpIzOnTuHHSElNGnUgP+8NDnsGFK2xJqAXZOzi8gupk6dygUXXMDYsWNp1KhR2HGkBGKN3nkZ/Nblo727rwmW9wCeLJV0IsLP639hYpf1YceQFHPJO2EnkDKoppkdTOTRjhrBawu+aoSaTERSwtatWxk5ciTXXXcd9erVY+7cudSuXTvsWJIA8QzksmduwRf4CWiZpDwiIiKSHGuAscHrH6Ne5y6LSAU2Y8YM+vTpwzfffEP79u05//zzVfCVI/EUfTPNbBrwXLB8HjAjeZFEREQk0dz9hLAziEjq2bhxI9deey2PP/44e++9N7Nnz+bYY48NO5YkWDyjd14J/BPoGHyNd/erkh1MRERESoeZNQ07g4iE46qrruKpp57ixhtvZMmSJSr4yqlYo3eauzuAu08GdhkxIPo9IiIiUmY9BpwWdggRKR0//fQTWVlZNG/enLvuuovBgwdzyCGHhB1LkihWS99/zewqM/vD83tmVtXMupjZU8DfkhtPREREks3dVfCJVADuzsSJE9l///254oorAGjVqpUKvgogVtF3KpANPGdmP5jZcjP7GvgSOB94wN2fLM5JzewcM1tmZjlmlp7P9pZmtsXMrivO8UVERGRXZpZmZo2jlquaWV8zW5GAY+vaLpLCvv32W/7yl7/wt7/9jf3335/77rsv7EhSimJN2bADGAeMM7MqQGNgu7tvTMB5PwW6A48WsH0s8GYCziMiIiKAmf2VyHV3q5l9CYwAHgc+Bi5MwCl0bRdJUf/973/p1q0b7s5DDz1E//79qVSp0KE9pByJZ/RO3D2TyFDPCeHuKwDMbJdtZnYm8DWwNVHnExEREW4BDnX3lWZ2CPA+cLa7v5qIg+vaLpJ6srOzSUtL45BDDuHMM8/kzjvvpHXr1mHHkhCkVIlvZrWBG4Db43hvXzObb2bz165dm/xwIiIiZdtOd18J4O4LgS8TVfDFomu7SOnLzMxk5MiRHHXUUezcuZN69erx9NNPq+CrwOJq6SsOM5sB5DcE9M3uPqWA3YYD97v7lvzuFEZz9/HAeID09HSNICoiIhJbEzO7Jmq5fvSyu4/NZ58/0LVdJPUtWrSIXr16sWjRInr06MG2bduoWrVq2LEkZIUWfWZ2FfBvd/+lKAd295OKkedw4Gwzuw+oD+SY2Q53f7gYxxIREZHf/QuoE2O5ULq2i6SujIwM7rjjDu69914aN27MpEmT6NGjR9ixJEXE09K3O/CxmS0k8sD3tGTNzefuv80GaWbDgS26KIiIiJScuxfavTJJ59W1XaQUmBmvvfYaF198MWPGjKFhw4ZhR5IUUugzfe5+C7A3kYlbLwW+NLO7zaxdcU9qZmeZ2WrgSOB1M5tW3GOJiIhI4cysbyLeE2NfXdtFStmWLVsYOnQoGzdupGrVqsybN48nnnii0IIvKzuH+d9s4NZXljL05aV8+PV6dmbllFJqCUO8o3e6mf0I/AhkAQ2ASWb2trsPKepJ3X0yMLmQ9wwv6nFFRESkQDea2boY2w0YRPBMXVHp2i5SuqZNm0bfvn1ZtWoVHTt25LzzzqNWrVpx7bvou4389V8fkJ0T6bz33Mff8WzvIziyXaNkRpYQxfNM3yDgEmAdMAG43t0zzawSkYnai1z0iYiISKl7F+hayHveLo0gIlJ8GzZsYPDgwUycOJH99tuPOXPmcPTRRxfpGC8tXP1bwQfgDs98+K2KvnIsnpa+hkB3d/82eqW755jZ6cmJJSIiIonk7peFnUFESm7gwIE8//zz3Hzzzdxyyy1Ur169yMfYmb1rV85Mde8s1+KZp+9BYLOZNYz6qgK/T8QqIiIiIiLJ8eOPP/L9998DcPfddzN//nzuuuuuYhV8AGcf2mKXdRce0apEGSW1xVP0LQTWAl8Q6c65FvjGzBaa2aHJDCciIiIiUlG5O08++ST7778//fv3B6Bly5YcdNBBJTpueqsGPNP7cE5pvzsn7teEiT070amNRvssz+Lp3vk2MMndpwGY2SlAD+AJYByR+XdERERERCRBvvnmG/r27cvbb7/Nsccey6hRoxJ27KqV0zh6r8Yc2TbyDF+lSpawY0tqiqfoO8Ld++QuuPt0Mxvt7pebWbUkZhMREZEEMbMWQGt3fy9YvgaoHWx+1t1XhhZORP7gnXfeoVu3bpgZjzzyCP369aNSpXg66BWNir2KI55Pzxozu8HMWgVfQ4CfzCwN0BOfIiIiZcMooH7U8uXAVsCBUCZuF5E/ys7OBuDQQw+lR48eLFu2jP79+xdY8G3ctpMPvlrPtGVr+PzHzeREjcgpEi2elr4LgGHAK0QuDHODdWnAuUlLJiIiIom0r7u/FrW8zd3HAJjZnJAyiQiQmZnJfffdx5QpU3jvvfeoV68eTz31VMx91m/NYMRrK3h5UWSAl6pplXj80nSO2Xu30ogsZUzMlr6gNe9Bd7/K3Q9290OC12vdfae6goiIiJQZeYf5OzHqdePSDCIiv1uwYAHp6enccssttGnThu3bt8e134ofNv1W8EFkGoahk5eyfktGsqJKGRaz6HP3bKCVmVUtpTwiIiKSHJvNbJ/cBXffAGBm+wGbQ0slUkFlZGRw4403cvjhh7N27VomT57MCy+8QL169eLaf+2Wnbus+27DdjbvyEp0VCkH4une+RUw18ymEun7D4C7j01aKhEREUm0YcBrZjaCyHRMAIcCQ4FBoaUSqaAqVarEtGnTuPTSSxk9ejT169cv0v6tG9XcZd0xezVmtzoaZ1F2Fc9ALv8DXgveWyfqS0RERMoId38L6E6kW+eTwVcXoLu7vxleMpGKY/Pmzdx444388ssvVKlShblz5zJhwoQiF3wA7feoy/3ndqRu9UgbziEt63Pr6ftTq1o8bTpS0RT6qXD32wHMrKa7b0t+JBEREUkGd/8UuCTsHCIV0Ztvvsnll1/O6tWrOfjggznvvPOoWXPX1rp4VauSxlmHtCC9dUO2ZmSxR/0a1KtRJYGJpTwptOgzsyOBx4jM5dPSzDoCl7t7/2SHExERkcQws1eJjMKdL3fvVopxRCqM9evXM3jwYJ5++mnat2/PvHnzOOKIIxJ2/D0bFr9wlIojnu6dDwB/BtYDuPsS4LgkZhIREZHEGw2MAb4GtgP/Cr62EHmUQ0SSYNCgQTz33HPceuutLFy4MKEFn0i84ur06+6rzCx6VXZy4oiIiEgyuPu7AGY2xt3Toza9ambzQ4olUi798MMP5OTk0KJFC+655x6GDBlChw4dwo4lFVg8LX2rzOwowM2sipldB6woyUnN7BwzW2ZmOWaWnmdbBzN7P9i+1MzyziskIiIixVfLzNrmLphZG6BWSQ+qa7sIuDuPPfYY7du3p3//yJNQe+65pwo+CV08LX39gAeB5sD3wHRgQAnP+ymREcQejV5pZpWBfwMXu/sSM2sEZJbwXCIiIvK7wcAsM/sKMKAVcHkCjqtru1RoX331FX379mXmzJkcf/zxjBkzJuxIIr+JZ/TOdcCFiTypu68AyNNlFOAU4JPguUHcfX0iz1uYOh8/XpqnExERKXXu/paZ7Q3sF6z6zN0zEnDclLy2i5SGmTNn0q1bN9LS0vjnP/9Jnz59qFQpng51IqUjntE7dwP6AK2j3+/uPZOQZx8i3UinAbsBz7v7fQXk6gv0BWjZsmVCTr75sGT8kaQs040AESkvzKx7AZvamRnu/nKSTh3qtV0kmbKysqhcuTLp6emcd9553HHHHbRo0SLsWCK7iKd75xRgDjCDIgzgYmYzgKb5bLrZ3afEyHMMcBiwDZhpZgvcfWbeN7r7eGA8QHp6eoFDUIuIiAgAXYPvTYCjgJlEuneeAMwDCi36dG0Xidi5cyf33nsvU6ZMYd68edSrV4/HH9eNYkld8RR9Nd39hqIe2N1PKkae1cDsoEspZvYGcAiRC5OIiIgUk7tfBmBm04H27r4mWN4DeDLOY+jaLhXexx9/TK9evVi6dCnnn38+27dvp2rVqmHHEokpns7Gr5nZ/yU9ScQ04EAzqxk8+H08sLyUzi0iIlIR7Jlb8AV+ApLZl1LXdikXduzYwfXXX88RRxzBhg0bmDp1Ks8++yz16tULO5pIoeIp+gYRKfx2mNkmM9tsZptKclIzO8vMVgNHAq8H/fxx91+AscDHwGJgobu/XpJziYiIyB/MNLNpZnapmV0KvE7kEY4S0bVdyru0tDRmzJhB7969WbZsGV27di18J5EUEc/onXUSfVJ3nwxMLmDbv4kM7SwiIiIJ5u5XmtlZwHHBqvHBdbmkx9W1XcqdTZs2cdddd3HTTTfRoEED5s2bR40aNcKOJVJk8YzeaUSmbGjj7nea2Z7AHu7+UdLTiYiISMLFKtBEJOK1116jX79+rFmzhsMOO4xzzjlHBV+UNRu3szM7h2b1alClsqanSHXx/AuNI9JV44JgeQvwSNISiYiIiIiEZO3atVxwwQV07dqVBg0a8P7773POOeeEHStlbMnI4rmPvuPUB+dw4ph3GfbqMlb/si3sWFKIeIq+w919ALADfuubryGKRERERKT0ZWfBj0th+VT4dh5s/zWhhx88eDCTJk1i+PDhLFiwgE6dOiX0+GXdklUbuenlpfy6PZOsHOfZD7/jhY9X4a5ZVlJZPFM2ZJpZGuDw22TtOUlNJSIiIiKSny/eghcvgZxg+uj03nDibVCj+KNorl69Gndnzz33ZOTIkdx4440ccMABCQpcviz89pdd1r20YDWXHtWaRrWrhZBI4hFPS9/fifT7b2JmI4D3gLuTmkpERESSwsyONrO3zewLM/vKzL42s6/CziUSl1+/h9cG/V7wAcyfAD8tK9bhcnJyGD9+PH/605+48sorAWjRooUKvhia1d/1uca9mtSmZtV42pIkLPGM3vmMmS0ATgQMONPdVyQ9mYj85pJ3GoUdQUTKj8eAwcACILuQ94qklh2/wtZ1u67furbIh1q5ciV9+vRh1qxZnHDCCYwdOzYBAcu/9NYN2K9pbT77cQsA1atUYtBJ+1CjalrIySSWuEpyd/8M+CzJWUSkABO7rA87gqQY3QiQEvjV3d8MO4RIsdRtBnt0hDVLfl9nlaBR2yIdZsaMGXTr1o0qVarwr3/9i169ehEZsF4K06pRLR6/tBPLf9jE9sxs9tm9Dvs2TfgMb5JgaocVERGpWP5rZqOAl4GM3JXuvjC8SCJxqlEfzngEXukPP34CNRtB1wdht/3i2j0rK4vKlSvTqVMnLrjgAm6//XaaN29e4ljZOc4367fy67ZM9qhXnT3y6QJZnjSrXyPfbp6SulT0iYiIVCyHB9/To9Y50CWELCJF1/RAuGQqbP4BqteDei0K3SUjI4N77rmHV199lffff5+6desyYcKEhMTJyMzm5UXfM3zqMjKycmhSpxr/vOhQDmnVICHHF0kEFX0iIiIViLufEHYGkRKr2SDyFYcPP/yQXr16sWzZMi688EK2b99O1aoFzz72/cbtZBVh0vEvftrMTS8v/W35580ZXPfiYl7sd5RGs5SUUWjRZ2abCaZriPIrMB+41t014peIiEgZYWbX5LP6V2CBuy8u5TgiSbNjxw6GDh3KAw88QPPmzXnttdc47bTTCnz/5u2ZTF78PaPe+pxtmdmcd9ie9O/cjhYNasY8z+pftu+y7qt121i7JUNFn6SMeKZseAC4HmgOtACuA54FngceT1oyERERSYZ0oB+R63pz4HLgVOBfZjYkzGAiiZSWlsa7775Lv379WLZsWcyCD2Dhdxu5bcoyNmdkkR1MOv7ywu8LPc/u9arvsm6PetVpWLPg1kSR0hZP0dfN3R91983uvsndxwN/dvcXAHVWFhERKVtaAIe4+7Xufi1wKNAEOA64NMxgIiW1ceNGrr32Wn755ReqVKnC3LlzGTduHHXr1i1034++2bDLupcWrubXbTtj7rfv7nW47pR9yB38s2bVNEad3ZEmdXctBkXCEs8zfdvM7FxgUrB8NrAjeJ2326eIiIiktiZEjdoJZAK7u/t2M8soYB+RlDd16lSuuOIKfvzxR4488kjOPvtsqlePv/Bq1XDXbpz77l6H6oXMP1erWmV6H9uGzvs2YcPWnezZsCatG8XuEipS2uIp+i4EHgTGESnyPgAuMrMawJVJzCYiIiKJ9wzwoZlNCZa7As+aWS1geXixRIrn559/ZuDAgbzwwgt06NCBKVOmkJ6eXviOeXRq25B9dq/NFz9FJh2vWTWNKzq3o1rlwicdr16lMgc0r1fkc4qUlkKLvmCglq4FbH4vsXFEREQkmdz9TjN7Ezg6WNXP3ecHry8MKZZIsV1zzTVMnjyZO++8kxtuuIEqVaoU6zitG9Xiycs6sWLNJnZk5rDP7rXZe3dNOi7lQzyjd+4G9AFaR7/f3XsW96Rmdg4wHNgf6JR7sTGzKsAE4JDgXBPd/Z7inkdEREQizKyuu28ys4bAV8FX7raG7r7rA01FO76u7VJqVq1ahbvTsmVLRo4cydChQ2nfvn2Jj6tJx6W8iqd75xRgDjADyE7QeT8FugOP5ll/DlDN3Q80s5rAcjN7zt2/SdB5RUREKqpngdOBBfzxmXwLltuW8Pi6tkvS5eTkMH78eIYMGULnzp2ZOnUqLVoUPjm7SEUXT9FX091vSORJ3X0FgOUOcxS1CahlZpWBGsBOYFMizy0iIlIRufvpwfc2STq+ru2SVF988QV9+vRh9uzZnHTSSTz44INhRxIpM+KZsuE1M/u/pCeJmARsBdYA3wGjC+puYmZ9zWy+mc1fu3ZtKcUTEREp28zs6GDQFszsIjMba2Ytk3hKXdulxN5++206duzIkiVLeOyxx5g+fTpt2iTl/oVIuRRP0TeISOG33cw2mdlmMyv0Dp2ZzTCzT/P5OiPGbp2IdCFtBrQBrjWzfLubuPt4d0939/Tddtstjj+GiIiIAP8gMh1TR+Ba4H/A0/HsqGu7lLbMzEwADj/8cC6++GKWL19Oz54982tRFpEY4hm9s1jDFrn7ScXY7QLgLXfPBH42s7lAOlEPm4uIiEiJZLm7B4Xaw+7+mJn1imdHXdultGRkZHDXXXfx2muv8cEHH1C3bl3Gjx8fdiyRMqvAlj4z2y/4fkh+X0nK8x3QJThvLeAI4LMknUtERKQi2mxmNwEXA6+bWSWgeGPcx0fXdimS999/n4MPPpi77rqLDh06kJGREXYkkTIvVvfOa4PvY/L5Gl2Sk5rZWWa2GjiSyAVnWrDpEaC2mS0DPgaecPdPSnIuERER+YPzgAygp7v/CLQARpX0oLq2S0lt376dq6++mqOPPpqtW7fy5ptv8tRTT1G3bt2wo4mUeQV273T3PsH3ExJ9UnefDEzOZ/0WIkM7i4iISBK4+49m9hKwd7BqHflck4txXF3bpUQqV67Me++9R//+/bnnnnuoU0cTo4skSoFFn5l1j7Wju7+c+DjhadCoMXz8eNgxJMU0aNQ47AgiIgllZn2AvkBDoB3QHPgncGKYuaRi+uWXX7j99tu57bbbaNiwIXPnzqVatWphxxIpd2IN5NI1+N4EOAp4J1g+AZgHlKuib/JLk8KOkDI6d+7MrFmzwo4hIiLJMYDIiJofArj7l2bWJNxIUhFNnjyZ/v37s3btWo499lh69Oihgk8kSQp8ps/dL3P3y4g83N3e3Xu4ew/gTyT3gW8RERFJngx335m7EEya7iHmkQrmp59+4txzz6V79+40bdqUjz76iB49eoQdS6Rci2eevj3dfU3U8k9AMidxFRERkeR518yGAjXM7GTgReDVkDNJBXLttdcyZcoURowYwUcffcQhhyRrUHgRyVXoPH3AzGAErueC5fOAGcmLJCIiIkl0I9ALWApcDrwBTAg1kZR73377LQCtWrXi3nvv5ZZbbmG//fYLOZVIxRHP5OxXBoO6HBusGh+M0CUiIiJljLvnAP8KvkSSKicnh3HjxnHjjTfSpUsXpk6dSvPmzcOOJVLhxNPSlztSZ7kauEVERKQiMbOlxHh2z907lGIcqQA+//xzevXqxdy5c/nzn//MQw89FHYkkQqr0KIvaOW7l8gonhZ8ubtrpkwREZGy4/Tg+4Dg+9PB94vQQC6SYNOnT6dbt27UrFmTJ598kksuuQQzCzuWSIUVT0vffUBXd1+R7DAiIiKSHO7+LYCZnezuB0dtusHMFhJ51k+kRDIzM6lSpQpHHnkkl112GcOGDaNp06ZhxxKp8OIZvfMnFXwiIiLlhpnZ0VELRxHf/wdECrRjxw6GDh1Keno6GRkZ1KlTh3/84x8q+ERSRDwtffPN7AXgFSAjd2XwnJ+IiIiULb2Ax82sHpFHNn4BeoYbScqyuXPn0qtXLz7//HMuvfRSMjIyNMm6SIqJp+irC2wDTola52hgFxERkTLH3RcAHYOiD3f/NeRIUkZt376dIUOG8Mgjj9CyZUumTZvGKaecUviOIlLq4pmy4bLSCCIiIiKlx91/NbPX+H2AF5EiqVKlCh9++CFXXXUVI0aMoHbt2mFHEpECFFj0mdkQd7/PzB4in1G93H1gUpOJiIhIsmnCNCmSDRs2MGzYMIYPH06jRo2YM2eOunKKlAGxWvpyB2+ZXxpBREREpNQtCjtAheUOG78Dz4F6LSCtStiJCjVp0iQGDBjAhg0bOOGEE+jevbsKPpEyosDRutz91eD7U+7+FDAZeDlqudjMbJSZfWZmn5jZZDOrH7XtJjNbaWafm9mfS3IeERER+SMzG5T72t175l0npWDbBpj7dxh3BDxyGEy/FX79PuxUBVqzZg09evTgnHPOoUWLFnz88cd079497FgiUgSFDtFsZulmthT4BPjUzJaY2aElPO/bwAHu3gH4ArgpOFd74K/An4BTgXFmllbCc4mIiMjv/pbPuktLelDd0C2Cb+fBjNsgcxtkZ8KH/4AVr4adqkDXXXcdb7zxBvfeey8ffvghBx10UNiRRKSI4pmX53Ggv7u3dvdWwADgiZKc1N2nu3tWsPgB0CJ4fQbwvLtnuPvXwEqgU0nOJSIiImBm55vZq0AbM5sa9TUL2JCAU+iGbry+nL7ruiXPQub20s9SgG+++YZvvvkGgFGjRrFkyRKGDBlC5crxDPwuIqkmnp/cbHefk7vg7u+ZWVasHYqoJ/BC8Lo5kSIw12r0kLmIiEgizAPWAI2BMVHrNxPpzVMi7h5dyXwAnB28/u2GLvC1meXe0H2/pOcss5rst+u63Q+EtKqlnyWP7OxsHnnkEYYOHUqXLl2YOnUqzZo1CzuWiJRQrNE7DwlevmtmjwLPERnF8zxgVmEHNrMZQNN8Nt3s7lOC99wMZAHPFC02mFlfoC9Ay5Yti7q7iIhIheLu3wLfmtlJwHZ3zzGzfYD9gKUJPl2xbuhWmGv7XidDg/Hwy9eR5er1oVMfqBRuA+iKFSvo3bs38+bN49RTT+Xhhx8ONY+IJE6slr4xeZaHRb3eZQqHvNz9pFjbzexSInMDnejuucf7Htgz6m0tgnX5HX88MB4gPT290DwiIiICwGzgWDNrAEwHPiZyQ/fCwnZM9g3dCnNtb7w3XDIVfvoUcrKgSXtovFeokaZNm0a3bt2oXbs2Tz/9NBdeeCFmFmomEUmcAos+dz8hWSc1s1OBIcDx7r4tatNU4FkzGws0A/YGPkpWDhERkQrI3H2bmfUCxgVz8i6OZ8dk39CtUBq0jHyFbOfOnVStWpWjjjqKPn36cNttt9GkSZOwY4lIgsUzkEsyPAzUAd42s8Vm9k8Ad18G/AdYDrwFDHD37JAyioiIlEdmZkcSadl7PVhX4n6FUTd0u+VzQ/evZlbNzNqgG7opYfv27dxwww0ceuih7Nixgzp16vDwww+r4BMpp0IZgsndC+zD4O4jgBGlGEdERKQiuZrIyJqT3X2ZmbUF/puA4z4MVCNyQxfgA3fvF5wj94ZuFrqhG7rZs2fTu3dvvvzyS3r37k1mZibVq1cPO5aIJJHG3RUREalA3P1dIoO01Taz2u7+FTAwAcfVDd0Ut23bNq677jr+8Y9/0KZNG2bMmMGJJ54YdiwRKQWFFn1mVhO4Fmjp7n3MbG9gX3d/LenpRIQmjRpwyTthp5BU06RRg7AjSBllZgcCE4GGkUVbC1wSPGIh5VjVqlVZsGABgwcP5s4776RWrVphRxKRUhJPS98TwALgyGD5e+BFQEWfSCn4z0uTw46QMjp37sysWbPCjiFS1j0KXOPu/wUws87Av4CjQswkSbJu3TqGDRvGHXfcQaNGjZgzZw5Vq4Y/H6CIlK54BnJp5+73AZkAwcPZGsNXRESkbKqVW/ABuPssQE0+5Yy785///If27dszfvx4Zs+eDaCCT6SCiqfo22lmNQjm5jOzdkBGUlOJiIhIsnxlZreaWevg6xbgq7BDSeL88MMPdO/enfPOO49WrVqxYMECzjrrrLBjiUiI4uneOYzI9Al7mtkzwNHApckMJSIiIknTE7gdeJnIDd05wTopJ4YMGcJbb73FqFGjuPrqq6lcueyP2/ftuq28veIn5v5vPV323Y0T9mtCiwY1w44lUmYU+lvA3d82s4XAEUS6dQ5y93VJTyYiIiIJY2bVgX7AXsBS4Fp3zww3lSTKV199RaVKlWjdujX33Xcfw4YNY++99w47VkKs35LB4P8sZuF3GwH472c/c8rKdYw9pyO1q1cJN5xIGVFo906LTLbzF+DQYMTOmmbWKenJREREJJGeAtKJFHx/AUaFG0cSITs7m/vvv58DDjiAgQMjM280a9as3BR8AP9bu/W3gi/X9GU/8c36beEEEimD4mnvHwfkAF2AO4DNwEvAYUnMJSIiIonV3t0PBDCzx4CPQs4jJbRs2TJ69erFhx9+yGmnnca4cePCjpQknv/a/FeLSD7iGcjlcHcfAOwAcPdfAA39JCIiUrb81pXT3bPCDCIl99Zbb3HwwQfzv//9j2effZZXX32VFi1ahB0rKdruVpsOzev9YV2X/ZrQurGe6ROJVzwtfZlmlsbvo3fuRqTlT0RERMqOjma2KXhtQI1g2QB397rhRZN4ZWRkUK1aNY455hj69evHrbfeym677RZ2rKRqXLsaD55/MG8sXcOcL9dycvumnNK+CXX0PJ9I3OIp+v4OTAaamNkI4GzglqSmEhERkYRy97SwM0jxbdu2jWHDhvHmm28yf/58ateuzd///vewY5WaNo1rMeCEvRhwwl5hRxEpk2IWfWZWCfgaGAKcSORu4JnuvqIUsomIiIhUeLNmzaJPnz6sXLmSvn37kpWl3rkiUjQxiz53zzGzR9z9YOCzUsokIiIiUuFt27aNa665hkcffZR27drxzjvvcMIJJ4QdS0TKoHgGcplpZj2CqRtEREREpBRUrVqVxYsXc+211/LJJ5+o4BORYoun6LsceBHIMLNNZrY56kFwEREREUmQtWvX0q9fP9avX0/lypWZM2cOo0ePpmZNjVQpIsVXYNFnZkcHL3dz90ruXtXd67p7nZKO8GVmo8zsMzP7xMwmm1n9YP3JZrbAzJYG37uU5DwiIiJSOnRtLxl357nnnqN9+/Y8/vjjzJkzB4AqVTRCpYiUXKyWvtwhoeYl4bxvAwe4ewfgC+CmYP06oGsweezfgKeTcG4RERFJPF3bi2n16tV069aNCy64gHbt2rFo0SLOPPPMsGOJSDkSayCXTDMbD7Qws13GBHb3gcU9qbtPj1r8gMg0ELj7oqj1y4jMIVTN3TOKey4RERFJPl3bi+/GG29k5syZjB07loEDB5KWptk1RCSxYhV9pwMnAX8GFiQxQ0/ghXzW9wAWFnRRMLO+QF+Ali1bJi+diIiIFFWxru0VycqVK0lLS6NNmzaMGjWKO+64g7Zt24YdS0TKqQKLPndfBzxvZivcfUlRD2xmM4Cm+Wy62d2nBO+5GcgCnsmz75+Ae4FTYuQbD4wHSE9P96LmExERkaJJ9rW9ItzQzcrK4oEHHuDWW2/l5JNPZurUqeyxxx5hxxKRci7mPH0AxSn4gv1OirXdzC4l0pp4ort71PoWwGTgEnf/X3HOLSIiIomX7Gt7eb+hu3TpUnr16sXHH39Mt27dGDduXNiRRKSCKLToSwYzOxUYAhzv7tui1tcHXgdudPe5YWQTERGRotO1PbY333yTbt260aBBA55//nnOPfdcNAWyiJSWeObpS4aHgTrA22a22Mz+Gay/EtgLuC1Yv9jMmoSUUUREROKna3s+duzYAcCxxx7LlVdeyfLlyznvvPNU8IlIqSq0pc/MBgFPAJuBCcDBRO7WTY+5YwzuvlcB6+8C7irucUVERCQcurb/0datW7n11luZNm0aCxYsoHbt2tx///1hxxKRCiqelr6e7r6JyIPXDYCLgZFJTSUiIiJSRs2cOZMDDzyQ+++/n+OPP57s7OywI4UmMzuHJas28vLC1cxc8RM/btoRdiSRCimeZ/py+x/8H/C0uy8z9UkQERER+YNt27YxaNAgJkyYwN577827777LcccdF3asUL37+Vr6Pj2fnGBYniPaNuSBvx5M07rVww0mUsHE09K3wMymEyn6pplZHSAnubFEREREypZq1aqxbNkyhgwZwpIlSyp8wbd+Swa3Tfn0t4IP4IOvNrDs+1/DCyVSQcXT0tcLOAj4yt23mVkj4LKkphIREREpA37++WduueUW7r77bho3bszs2bOpXDmUwdFTzrad2fl25/x1e2YIaUQqtkJb+tw9B2hNZNStMcBx7v5JsoOJiIiIpCp359///jf7778/Tz31FPPmzQNQwRelSd1qdO3Y7A/rKhm02612SIlEKq5Ciz4zGwf0A5YCnwKXm9kjyQ4mIiIikopWrVrF6aefzsUXX8y+++7L4sWL6datW9ixUk61ymlcfdLenHFQMyoZNK9fg/EXp9O+Wd2wo4lUOPHcjuoC7O/uDmBmTwHLk5pKREREJEXddNNNzJo1iwcffJABAwaQlpYWdqSU1aZxbe47uwPXnbIvNaum0ah2tbAjiVRI8QzkshJoGbW8J/BlcuKIiIiIpJ4vvviCr776CoDRo0fz6aefMnDgQBV8cahWOY09G9ZUwScSogKLPjN71cymAnWAFWY2y8xmASuCdSIiIiLlWlZWFvfeey8dOnTg6quvBqBp06a0adMm3GAiIkUQq3vn6FJLISIiIpJilixZQs+ePVm4cCFnnXUWjzyiIQ1EpGwqsOhz93dzX5tZU6AT4MDH7v5jKWQTERERCcUbb7zBGWecQaNGjZg0aRI9evQIO5KISLHFM3pnb+AjoDtwNvCBmfVMdjARERGRZPth43ZmrviJV5f8wOc/bmLbtm0AHHfccQwcOJDly5er4BORMi+e0TuvBw529/UAweTs84DHkxlMREREJJlWbdhGv38vYNkPm8jZuZ3N7/2bBr+sYPnSJdSuXZsxY8aEHVFEJCHiKfrWA5ujljcH60RERETKrEXf/cKyHzax/etFrJ/2MNm//kTjzmezaWsG1atXDzueiEjCFFj0mdk1wcuVwIdmNoXIM31nAJ+UQrYKqXPnzmFHAFInx6xZs8KOICIi5dS3P21g3RsPsHXpDCo3bMHuF95L/f0OgaqaWkBEypdYLX250zL8L/jKNSV5cURFjoiISOk4uO3uZG34nrpHnEP9o8/HKlel+6HNaVxLRZ+IlC+xRu+8PVknNbNRQFdgJ5GC8jJ33xi1vSWwHBju7po6QkREJMWVlWv7jz/+yM0338zIkSM5pFVDnpz0OvdO/5JNO7I4+9DmXHR4KypVsrDiiYgkRazunQ+4+9Vm9iqRbp1/4O7dSnDet4Gb3D3LzO4FbgJuiNo+FnizBMcXERGR0pXS13Z3Z+LEiQwePJht27Zx5pln0rVrV/56RBuO378pO7Ny2KNedapWTgsroohI0sTq3vl08D3hd+PcfXrU4gdEpoIAwMzOBL4Gtib6vCIiIpIcqXxt/+abb7j88suZPn06xxxzDBMmTGDffff9bfse9WqEEUtEpNTE6t65IPj+bkHvSZCewAsAZlabyF3Bk4HrYu1kZn2BvgAtW7ZMckQREREpgmJd25PllltuYd68eTz88MNcccUVVKpU6DTFIiLlSqzunWcALdz9kWD5Q2C3YPMQd58U68BmNgNoms+mm919SvCem4Es4Jlg23DgfnffYha7P727jwfGA6Snp+/S/VREREQSK9nX9kTe0P3888+pXLky7dq1Y/To0YwYMYJWrVqV6JgVzc6sbJZ+/ytLv99EvRpVOGTP+rRqXCvsWCJSDLG6dw4B/hq1XA04DKgFPAHELPrc/aRY283sUuB04ER3zy3aDgfONrP7gPpAjpntcPeHYx1LREREki/Z1/ZE3NDNzMxk9OjR3H777fz5z39mypQpNG2aX50qhZn95Tr6TJxP7r9kq0Y1mdizE60aqfATKWtiFX1V3X1V1PJ77r4eWG9mJfppN7NTiRSVx7v7ttz17n5s1HuGA1tU8ImIiKS+VLi2L1q0iJ49e7J48WLOPvtsHn5Y/4Uoro3bdnLPGyt+K/gAvl2/jU9W/6qiT6QMilX0NYhecPcroxZ3o2QeJtJy+HbQ1eMDd+9XwmOKSBJ17tw57AhA6uTQnJoiuwj12v76669zxhln0LhxY1566SW6d+9eWqculzKycli/decu67fsyAohjYiUVKyi70Mz6+Pu/4peaWaXAx+V5KTuvlcc7xleknOISGKpyBGRWMK6tm/bto2aNWvSuXNnBg8ezNChQ2nQoEHhO0pMTepU4+IjWvHQOyt/W1fJYP9mdUJMJSLFFavoGwy8YmYXAAuDdYcSuYt3ZpJziYiIiBRo8+bN3HTTTcyYMYNFixZRq1YtRo0aFXascsPMOL9TS9IqGc988B1N6lbjhlP344Bm9cKOJiLFEGvKhp+Bo8ysC/CnYPXr7v5OqSQTERERycdbb73F5ZdfzqpVqxg4cCDuGsQ7GZrVr8GgE/fmgsNbUqNyGnVqVAk7kogUU6yWPgCCIk+FnoiIiIRq69at9O/fn4kTJ7L//vszd+5cjjzyyLBjlWtmRpM61cOOISIlpNlJRUREpEyoXr06X331FbfccguLFi1SwSciEicVfSIiIpKy1qxZw2WXXcbatWtJS0tj1qxZ3HnnnVSrVi3saCIiZYaKPhEREUlJTzzxBO3bt+f555/ngw8+ACAtLS3kVCIiZY+KPhEREUk5X3zxBT179uTAAw9kyZIldO3aNexIIiJlloo+ERERSTlbt25l3LhxzJo1i3322SfsOCIiZZqVh2GOzWwt8G3YOcqRxsC6sEOI5EOfzcRq5e67hR1CJD9JuLan6u+PVM0FqZstVXNB6mZL1VyQutnKYq4Cr+vlouiTxDKz+e6eHnYOkbz02RSR4krV3x+pmgtSN1uq5oLUzZaquSB1s5W3XOreKSIiIiIiUo6p6BMRERERESnHVPRJfsaHHUCkAPpsikhxpervj1TNBambLVVzQepmS9VckLrZylUuPdMnIiIiIiJSjqmlT0REREREpBxT0SciIiIiIlKOqegrY8ws28wWm9mnZvaimdVM4LG3FHO/CWbWPlE5pGwp6WfSzFqb2QVFeO+nxcz5hpnVL86+IlI2mdkoM/vMzD4xs8l5fweYWUsz22Jm16VKNjM72cwWmNnS4HuXVMgVbLvJzFaa2edm9ufSzBWc/xwzW2ZmOWaWHrW+ipk9FfydrTCzm1IhV7Ctg5m9H2xfambVUyVbsD2Un4EY/5ahfv5jZQu2hfozEJXjIDP7IPj/13wz61TYPir6yp7t7n6Qux8A7AT6RW80s8qlHcjde7v78tI+r6SMmJ/JOLQG4ir6SsLd/8/dNyb7PCKSUt4GDnD3DsAXQN5iYCzwZqmniigo2zqgq7sfCPwNeDoVcgU3d/8K/Ak4FRhnZmmlnO1ToDswO8/6c4Bqwd/ZocDlZtY67FzB/8n+DfRz9z8BnYHMUsxVYLYoYf0MFJQr7M8/FPzvmQo/A7nuA25394OA24LlmFT0lW1zgL3MrLOZzTGzqcByM0sL7tR9HNypuzy/nc2sTXD3aamZ3ZVn2/VR+98erKtlZq+b2ZKgVee8YP2s3DshZtbLzL4ws4/M7F9m9nCw/kkz+7uZzTOzr8zs7GT+xUhocj+TDc3sleDz84GZdQAws+ODu1KLzWyRmdUBRgLHBusG5z2gmR0afOaWAAOi1uf7OTezPcxstv3e+nhssP4bM2scvL41uEv3npk9l3uHM/gs3xt8fr/I3VdEyiZ3n+7uWcHiB0CL3G1mdibwNbAshGgFZnP3Re7+Q7B+GVDDzKqFnQs4A3je3TPc/WtgJVBo60KCs61w98/z2wTUCoqsGkRuQG5KgVynAJ+4+5LgfevdPbu0chWSLdSfgYJyhf35j5WNFPgZiOJA3eB1PeCHGO8FVPSVWcEvtr8AS4NVhwCD3H0foBfwq7sfBhwG9DGzNvkc5kHgH8HdlDVRxz4F2JvIB/kg4FAzO47IXY0f3L1j0KrzVp5MzYBbgSOAo4H98pxvD+AY4HQi/9GXciTPZ/J2YFFwp3goMDF423XAgODO1LHAduBGYE7QWnh/Pod+ArjK3TvmWV/Q5/wCYFpwjo7A4jw5DwN6BNv+AuTt7lLZ3TsBVwPDivBXICKprSdBi4aZ1QZuIPK7KhX8li2PHsBCd88o5Ty5onM1B1ZFbVsdrEsFk4CtRP4v8x0w2t03hBsJgH0AN7NpZrbQzIaEHShXCv4M5Cfsz39eqfQzcDUwysxWAaPZtRfDLkq9K6CUWA0zWxy8ngM8BhwFfBTcdYDInaUOUa1p9YgUcV/zR0cT+YGCSPP5vVH7nwIsCpZrB/vPAcaY2b3Aa+4+J8/xOgHv5v6iNbMXifzCy/WKu+cQaY3cvUh/akll+X0mPyT4bLn7O2bWyMzqAnOBsWb2DPCyu682swIPbJFnSeq7e24Xi6eJFGpQ8Of8Y+BxM6tC5DO3mD86Gpji7juAHWb2ap7tLwffFxDpeioiKczMZgBN89l0s7tPCd5zM5AFPBNsGw7c7+5bYv0OCilb7r5/InJdPiWVciVbPNny0QnIBpoBDYA5ZjbD3b8KOVdlIje7DwO2ATPNbIG7z0xUrhJkG06SfwaKmSt336R9/kuarbTEygicCAx295fM7Fwi//c6KdbxVPSVPduDFozfBD+sW6NXEWkZmZbnfSOA0wCijpHfRI0G3OPuj+6ywewQ4P+Au8xsprvfUYTs0XdqkneVldJW0GdyF+4+0sxeJ/IZmmv5PARtZk8ABxPpqhDrWb98P+fBMY4j8ll/0szGuvvEXfYuWO7nNBv9jhRJee4e8z86ZnYpkR4mJ/rvkxMfDpxtZvcB9YEcM9vh7g+nQDbMrAUwGbjE3f+XyEwlyPU9sGfU21oE60o1WwEuAN5y90zgZzObS6QXR8KKvmLmWg3Mdvd1EBlQjEjPrIQWfcXMlvSfgWLmSvrnH4qdrVR+BnLFymhmE4FBweKLwITCjqfuneXTNOCKoKUDM9vHzGq5+81BF7qDgvfNJfJAKsCFefbvGTT9Y2bNzaxJ0H1zm7v/GxhF5BdXtI+B482sQdDVrwdSUc0h+EyZWWdgnbtvMrN27r7U3e8l8nnZD9gM1Mnd0d0vCz6nuQOvbDSzY4LNeT+nu3zOzawV8JO7/4vIL8G8n9O5QFczqx58xk9P6J9cRFKGmZ0KDAG6ufu23PXufqy7t3b31sADwN2JLviKmy3o4fA6cKO7zy3NTLFyAVOBv5pZtaAr/d7AR6WdrwDfAV0gMv4AkcdMPgs1UcQ04EAzqxn8v+h4ICUGvkuFn4H8hP35L0Qq/Qz8QOTzBJHP/peF7aCir3yaQOSXykKLDG//KPm3WAwCBpjZUqL6JLv7dOBZ4P1g2yQi/yk/EPgo6Mo3DPjD4C/u/j1wN5EfgLnAN8CvifyDSZkxnMizoJ8QeX7zb8H6q4PBVT4hMoLZm8AnQLZFBmvZZSAX4DLgkeBzF92EWNDnvDOwxMwWAecReXb1N+7+MZFf3J8E51+KPqci5dXDRK5fb1tkcKd/hh0oSkHZrgT2Am6z3we+ahJ2LndfBvyHyO/dt4g8n12qg5KY2Vlmtho4EnjdzHJ7ejwC1DazZURuKD7h7p+EncvdfyEyOubHRJ4vX+jur5dWrljZwhYjV9if/1j/nqH/DETpQ+SRqyVE/u/dt7AdLKo3gUiJmVntoH94ZSJN84+7++Swc4lEi/qc1iQyJHNfd18Ydi4RERGRZNDzKpJow83sJKA6MB14Jdw4Ivkab5H5dqoDT6ngExERkfJMLX0iIiIiIiLlmJ7pExERERERKcdU9ImIiIiIiJRjKvpERERERETKMRV9IiIiIlJiZpYdDLH/qZm9GIyQnKhjbynmfhOCgbsSysyGm9l1+axvHUwjlLvcycxmmdmXZrbQzF43swMLON73ZnZHsHypma0N/j4/K2BKI8zsSTP7Omp6g3n5vKezmb2Wz35n5/PewWb2nZmFPmefJJZG7xQRERGRRNju7gcBmNkzQD8i89QRrKvs7lmlGcjde5fm+aKZ2e5E5nW7wN3nBeuOAdoRmSM2r/vdfXTU8gvufqWZNQI+N7NJ7r4qn/2ud/dJicjs7veb2S9AeiKOJ6lDLX0iIiIikmhzgL2CVqY5ZjYVWG5maWY2ysw+NrNPzOzy/HY2szZm9r6ZLTWzu/Jsuz5q/9uDdbWCVrQlQUvjecH6WWaWHrzuZWZfmNlHZvav3NasoNXr72Y2z8y+yq8FLHjfzcH+7wH7Rq0/NDjvEmBA1C5XEpkW6LfWN3d/z91fKcpfpLuvB1YCexRlP5FoKvpEREREJGHMrDLwF35vzToEGOTu+wC9gF/d/TDgMKCPmbXJ5zAPAv9w9wOBNVHHPgXYG+gEHAQcambHAacCP7h7R3c/AHgrT6ZmwK3AEcDRwH55zrcHcAxwOjAynz/TocBfg3P+X5A91xPAVe7eMc9ufwJKPA+smbUkMq/sJwW8ZVRU985nSno+KZ9U9ImIiIhIItQws8XAfOA74LFg/Ufu/nXw+hTgkuB9HwKNiBRxeR0NPBe8fjpq/SnB1yIiBdV+wf5LgZPN7F4zO9bdf81zvE7Au+6+wd0zgRfzbH/F3XPcfTmwez55jgUmu/s2d98ETAUws/pAfXefnU/WPzCzD81shZk9WNB78jjPzD4h0so3zt13FPC+6939oODrwny2FzQptybrrkD0TJ+IiIiIJMJvz/TlMjOArdGriLSKTcvzvhHAaQBRx8ivKDHgHnd/dJcNZocQaYW7y8xmuvsdRciekeccibCMSCvnFAB3PzzoOnp6nPvnPtOXDkw3s6nu/mMxcqwHGuRZ1xBYV4xjSRmllj4RERERKS3TgCvMrAqAme1jZrXc/ebc1qrgfXOJdKcEuDDP/j3NrHawf3MzaxJ039zm7v8GRhEptqJ9DBxvZg2C7qc9iph7NnCmmdUwszpAVwB33whsDAZoyZv1EeBSMzsqal2RRzR19/lEWhAHFXXfwJdAMzPbH8DMWgEdgcXFPJ6UQWrpExEREZHSMgFoDSy0SDPgWuDMfN43CHjWzG4gaCkDcPfpQfHyftCKuAW4CNiLyLNtOUAmcEX0wdz9ezO7G/gI2AB8BuTtAlogd19oZi8AS4CfiRSRuS4DHjczB6ZH7fNjMKDMvWbWPNhvHVCUFshc9xL5O7sbuB/4Z1AMQuTPfUvUezsBHYB+7t7b3TPM7CLgCTOrTuTvp3duF9hgmoj57j61GLmkjDB3decVERERkfLNzGq7+5agpW8y8Li7Tw47F0Tm6QO25JmyIawslwLp7n5l2FkkcdS9U0REREQqguHBADKfAl8Dr4Sa5o+2AH2DVrfQBJPA3wRsCjOHJJ5a+kRERERERMoxtfSJiIiIiIiUYyr6REREREREyjEVfSIiIiIiIuWYij4REREREZFyTEWfiIiIiIhIOfb/miihDPCiQ8EAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1080x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "metric = \"ddg\"\n",
    "boxlabel_x = ''\n",
    "boxlabel_y = 'Gibbs free binding energy (ddG) [R.E.U.]'\n",
    "scattlabel_x = 'Pre-design ddG [R.E.U.]'\n",
    "scattlabel_y = 'Post-design ddG [R.E.U.]'\n",
    "\n",
    "make_plot(all_data, metric, boxlabel_x, boxlabel_y, scattlabel_x, scattlabel_y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### dSASA-normalized ddG"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Median pre-design: -16.64 / Median post-design: -16.18\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "metric = \"nddg\"\n",
    "boxlabel_x = ''\n",
    "boxlabel_y = 'dSASA-normalized ddG [R.E.U.]'\n",
    "scattlabel_x = 'Pre-design ddG-per-dSASA [R.E.U.]'\n",
    "scattlabel_y = 'Post-design ddG-per-dSASA [R.E.U.]'\n",
    "\n",
    "make_plot(all_data, metric, boxlabel_x, boxlabel_y, scattlabel_x, scattlabel_y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Interface hydrogen bonds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Median pre-design: 4.00 / Median post-design: 4.00\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "metric = \"hbonds\"\n",
    "boxlabel_x = ''\n",
    "boxlabel_y = 'Interchain H-bonds [Count]'\n",
    "scattlabel_x = 'Pre-design H-bonds [Count]'\n",
    "scattlabel_y = 'Post-design H-bonds [Count]'\n",
    "\n",
    "make_plot(all_data, metric, boxlabel_x, boxlabel_y, scattlabel_x, scattlabel_y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Buried unsatisfied polar atoms (Filter #1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Median pre-design: 4.00 / Median post-design: 3.00\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA3gAAAEGCAYAAAA32TfWAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuNSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/xnp5ZAAAACXBIWXMAAAsTAAALEwEAmpwYAABJkUlEQVR4nO3dd3hUZfrG8e9D7x1ceregUiOKWFB/unZ37QURaRZQEFHRlaJY1rJgwRUREHtBxA527CJFpEUsKCIqvbeQ5Pn9MSfuGFOGkMmZSe7Pdc2VmfeUuScMM3nOe877mrsjIiIiIiIiya9U2AFERERERESkcKjAExERERERKSZU4ImIiIiIiBQTKvBERERERESKCRV4IiIiIiIixUSZsAPsqTp16nizZs3CjiEiklTmzp271t3rhp1DJDt9r4uIxG7jxo38+OOPZGZm5vq9nnQFXrNmzZgzZ07YMUREkoqZLQ87g0hO9L0uIpI/d8fM+O6777jhhhuYNm1art/rOkVTREREREQkAe3evZvbbruNCy64AHendevWvPTSS3luowJPREREREQkwcydO5eUlBSGDRsGwK5du2LaTgWeiIiIiIhIgtixYwc33HADnTt3Zs2aNbz88ss899xzVKhQIabtVeCJiIhIoTKzGmb2opl9Y2apZtYl7EwiIolo9eadfLtqCxu3p/3Rtm3bNiZPnkyvXr1YsmQJZ5xxxh7tM+kGWREREZGEdz8ww93PNrNyQKWwA4mIJBJ355Pv1nLdiwv4ffNOWtYoxUEbP+c/tw2nTp06LFmyhNq1axdo33Et8MzsJ2ALkAGku3tKtuVG5EvgZGA70NPd58Uzk4iIiMSPmVUHjgJ6Arh7GpCW1zYiIiXND2u20eeJOexKz2THD7P58K2HeH/rerod2ZV/nvL3Ahd3UDQ9eMe4+9pclp0EtA5uhwIPBz9FREQkOTUH1gCPmVk7YC4w0N23hRtLRCRxrFi/ne2bN7DhvUfZtmQmZes0oe4/bqRF270vhcK+Bu8M4AmP+AKoYWb1Q84kIiIiBVcG6Ag87O4dgG3A0OgVzKyfmc0xszlr1qwJI6OISKhqVS7LmpfvZNs3n1C96wXU73k/NZu1oXrFsnu973j34Dnwtpk58Ii7j8+2vCGwIurxL0Hbb9ErmVk/oB9AkyZN4pe2CHXr1i3sCAll5syZYUeQKHp//pnenyJ75BfgF3efFTx+kWwFXvD3wHiAlJQUL9p4IiLh+fXXX6lWrRqt61XlsutGMmX+75Sr2wyAW884kKa19/6S5XgXeEe4+0ozqwe8Y2bfuPtHe7qT4vhFkCh/MHbr1i1hskjiSIT3hN6bIsnJ3X83sxVmtp+7LwWOA5aEnUtEJEzuzsSJExkyZAiXXnopY8aM4fa+p3Px71tYtXknjWtVYr99qhIZomTvxLXAc/eVwc/VZjYN6AxEF3grgcZRjxsFbSIiIpK8rgKeDkbQXAZcGnIeEZHQ/PDDD/Tt25cPPviAbt260b9/fwCqVChLSrNahf58cbsGz8wqm1nVrPvACcCibKu9CvSwiMOATe7+GyIiIpK03H2+u6e4e1t3/4e7bwg7k4hIGKZOncrBBx/M3LlzeeSRR3jvvfdo1apVXJ8znj14+wDTgm7GMsAz7j7DzC4HcPdxwJtEpkj4nsg0CTrCJyIiIiIiSc3dMTPatWvHKaecwpgxY2jUqFGRPHfcCjx3Xwa0y6F9XNR9B/rHK4OIiIiIiEhRSUtL484772Tx4sU8//zztGrViilTphRphrCnSRAREREREUl6X375JZ06dWLkyJGULVuWtLS0UHLk2oNnZg/EsP1md7+5EPOIiIiIiIgkje3btzN8+HDGjBlD/fr1ee211zj11FNDy5PXKZpnAMPz2X4ooAJPRERERERKpB07dvDUU0/Rt29f7rrrLqpXrx5qnrwKvDHu/nheG5tZzULOIyIiIiIiktA2bdrE2LFjueGGG6hduzapqanUrJkYpVGu1+C5+30AZtY1+7Kstqx1RERERERESoLXXnuNNm3aMHz4cD755BOAhCnuILZBVh6MsU1ERERERKRYWrNmDRdeeCGnn346tWvX5osvvqBbt25hx/qLvAZZ6QIcDtQ1s8FRi6oBpeMdTEREREREJFGcffbZfP7559xyyy0MHTqUcuXKhR0pR3ldg1cOqBKsUzWqfTNwdjxDiYiIiIiIhG3FihXUqFGDqlWrMmbMGMqXL8+BBx4Ydqw85VrgufuHwIdmNtndlxdhJhERERERkdBkZmYyfvx4rr/+enr16sV9991Hx44dw44Vk7x68LKUN7PxQLPo9d392HiFEhERERERCcN3331H3759+fDDDznuuOO4+uqrw460R2Ip8KYA44AJQEZ844iIiIiIiITjxRdf5OKLL6Z8+fJMmDCBXr16YWZhx9ojsRR46e7+cNyTiIiIiIiIhMDdMTM6dOjAGWecwejRo2nQoEHYsQoklmkSXjOzK82svpnVyrrFPZmIiIiIiEgc7dq1ixEjRnDOOefg7rRs2ZLnnnsuaYs7iK0H75Lg53VRbQ60KPw4IiIiIiIi8ffFF1/Qu3dvlixZwsUXX0xaWhrly5cPO9Zey7fAc/fmRRFEREREREQk3rZt28awYcO47777aNSoEW+++SYnnXRS2LEKTb4Fnpn1yKnd3Z8o/DgiIiIiIiLxs3PnTp599lmuuOIK7rzzTqpVqxZ2pEIVyymah0TdrwAcB8wDVOCJiIiIiEjC27hxIw888AA33XQTtWvXJjU1lRo1aoQdKy5iOUXzqujHZlYDeC5egURERCQ8ZnZmDKvtdPc34x5GRKQQvPzyy1x55ZWsXr2ao48+mqOPPrrYFncQWw9edtsAXZcnIiJSPD0KvALkNfHTUYAKPBFJaKtWreKqq65iypQptGvXjtdee41OnTqFHSvuYrkG7zUio2YClAYOAF6IZygREREJzXR375XXCmb2VFGFEREpqHPOOYdZs2Zx++23c91111G2bNmwIxWJWHrw7o26nw4sd/df4pRHREREQuTu3QHMrLy774peltWWtY6ISKL5+eefqVmzJlWrVuX++++nYsWK7L///mHHKlL5TnTu7h8C3wBVgZpAWrxDiYiISOg+j7FNRCR0mZmZ/Pe//+XAAw9k2LBhAHTo0KHEFXcQ2yma5wL3ADOJnI//oJld5+4vxjmbiIiIFDEz+xvQEKhoZh3437V41YBKoQUTkb2zfT2kbYMajcNOUui+/fZb+vTpw8cff8zxxx/PoEGDwo4UqlhO0fwXcIi7rwYws7rAu4AKPBERkeLn70BPoBEwOqp9C3BTLDsws5+C9TOAdHdPKdyIIhKz9DT4/l34ZDRsWwPtLoADz4S6+4adrFC88MIL9OjRg4oVK/LYY49xySWXYJbXGFHFXywFXqms4i6wjhhO7cxiZqWBOcBKdz8127KeRHoHVwZNY919Qqz7FhERkcLl7o8Dj5vZWe4+dS92dYy7ry2sXCJSQMs/hRe6Q2ZG5PHMOyFjNxw3LNxce8ndMTM6derEmWeeyX/+8x/q168fdqyEEEuBN8PM3gKeDR6fB0zfg+cYCKQSObUjJ8+7+4A92J+IiIjE3+tmdiHQjKi/F9z91tASicie+33B/4q7LF89AR0uhFotw8m0F3bu3MmoUaNITU1l6tSptGzZkmeeeSbsWAkllkFWrgMeAdoGt/Hufn0sOzezRsApgHrlREREkssrwBlERtDeFnWLhQNvm9lcM+uXfaGZ9TOzOWY2Z82aNYUWWERyULbyX9sqVIfSFYo+y1767LPP6NChA3fccQfVq1cnLU1jP+Yk1x48M2sF7OPun7r7S8BLQfsRZtbS3X+IYf/3AdcTGYEzN2eZ2VHAt8A17r4ihyz9gH4ATZo0ieFpRUREZC81cvcTC7jtEe6+0szqAe+Y2Tfu/lHWQncfD4wHSElJ8dx2IiKFoGFHqPo32PL7/9qOug6qNwwv0x7aunUrN910E2PHjqVJkya89dZbnHDCCWHHSlh59eDdB2zOoX1TsCxPZnYqsNrd5+ax2mtAM3dvC7wDPJ7TSu4+3t1T3D2lbt26+T21iIiI7L3PzOzggmzo7iuDn6uBaUDnwgwmInugYUc472k44XY4YjBc+AK0PinsVHskLS2NqVOnMmDAABYtWqTiLh95XYO3j7svzN7o7gvNrFkM++4KnG5mJwMVgGpm9lT05Kjuvi5q/QnA3bHFFhERkTg7AuhpZj8Cu4hMl+DBQdlcmVllIgO0bQnunwDouj2RMDVKidySyPr163nggQe4+eabqVWrFqmpqVSrltuQHhItrwKvRh7LKua3Y3e/EbgRwMy6AUOii7ugvb67/xY8PJ3IYCwiIiISvoIe4t8HmBYMU14GeMbdZxRaKhEp9qZOnUr//v1Zu3Ytxx57LEcddZSKuz2QV4E3x8z6uvuj0Y1m1gfI67TLPJnZrcAcd38VuNrMTidyAfd6IvPuiIiISPgKdG2cuy8D2hVyFhEpAX7//XcGDBjA1KlT6dChAzNmzKB9+/Zhx0o6eRV4g4gcgbuI/xV0KUA54J978iTuPhOYGdwfHtX+Ry+fiIiIJJQ3iBR5RuRSi+bAUuDAMEOJSPF17rnn8uWXX3LnnXdy7bXXUrZs2bAjJaVcCzx3XwUcbmbHAAcFzW+4+/tFkkxERERC4+5/GmDFzDoCV4YUR0SKqZ9++olatWpRrVo1HnjgASpWrMh+++0XdqykFss8eB+4+4PBTcWdiIhICeTu84BDw84hIsVDZmYmDz74IAcddBDDhg0DoH379iruCkFe8+DNc/eOeW0cyzoiIiKSfMxscNTDUkBH4NeQ4ohIMZKamkqfPn347LPPOPHEExk8eHD+G0nM8roG7wAzW5DHcgOqF3IeERERSQxVo+6nE7kmb2pIWUSkmHj++efp0aMHVapU4YknnqB79+4Eo+5KIcmrwNs/hu0zCiuIiIiIJA53vwXAzKoEj7eGm0hEkllmZialSpXikEMO4dxzz+Xee+9ln332CTtWsZTXICvLizKIiIiIJA4zOwh4EqgVPF4LXOLui0INJiJJZceOHdx6662kpqYybdo0WrRowZNPPhl2rGIt30FWREREpEQaDwx296bu3hS4NmgTEYnJJ598Qvv27fn3v/9N7dq1SUtLCztSiaACT0RERHJS2d0/yHoQzGlbObw4IpIstmzZwoABAzjyyCNJS0vjnXfeYeLEiZQvXz7saCVCzAWemVU2s9LxDCMiIiIJY5mZDTOzZsHtZmBZ2KFEJPGlp6czbdo0Bg0axKJFi/i///u/sCOVKLkWeGZWyswuNLM3zGw18A3wm5ktMbN7zKxV0cUUERGRItYLqAu8RGT0zDpBm4jIX6xbt45hw4axe/duatasyTfffMOYMWOoXFkd/0Utr1E0PwDeBW4EFrl7JoCZ1QKOAe4ys2nu/lT8Y4qIiEhRMLMKQFV3XwNcHdVeD9gRWjARSUjuzpQpUxgwYAAbNmzg+OOP56ijjqJq1ar5byxxkdcpmv/n7qPcfUFWcQfg7uvdfaq7nwU8H/+IIiIiUoQeAI7Mob0rMKaIs4hIAvv1118588wzOe+882jSpAlz587lqKOOCjtWiZdrgefuu3NbFjUnTq7riIiISFLq5O4vZW9092mA/nITkT+cd955zJgxg7vvvpsvvviCtm3bhh1JyPsUzbwsAZoUZhARERFJCJXyWKbRt0VKuB9//JHatWtTrVo1xo4dS6VKlWjdunXYsSRKrgWemQ3ObRFQJT5xREREJGSrzayzu38Z3WhmhwBrQsokIiHLyMjgwQcf5F//+hd9+vTh/vvvp127dmHHkhzk1YN3B3APkJ7DMh3BExERKZ6uA14ws8nA3KAtBegBnB9WKBEJz5IlS+jTpw+ff/45J598MkOGDAk7kuQhrwJvHvCyu8/NvsDM+sQvkoiIiITF3b80s85Af6Bn0LwYONTdV4cWTERC8dxzz3HJJZdQtWpVnnrqKS688ELMLOxYkoe8CrxLgXW5LEuJQxYRERFJAEEhNyLsHCISnszMTEqVKsWhhx7K+eefzz333EO9evXCjiUxyGsUzaXuvjaXZaviF0lERETCYmbjC2MdEUlO27dv5/rrr+ef//wn7k7z5s15/PHHVdwlkbwGWXkUeMDdF+awrDJwHrDL3Z+OYz4REREpWv8ws515LDfgmKIKIyJF58MPP6RPnz58//339OvXj927d1OuXLmwY8keyusUzYeAYWZ2MLCIyMhZFYDWQDVgEqDiTkREpHi5LoZ1Po57ChEpMlu2bOH6669n3LhxtGzZkvfff59jjtFxnGSVa4Hn7vOBc4NJzVOA+sAOINXdlxZNPBERESlK7v542BlEpGhlZGTw+uuvM3jwYEaNGkWlSnlNhymJLt+Jzt19KzAz/lFERERERKQorF27ljFjxjBy5Ehq1KhBamoqVapoquviIN8CT0RERGRPmVlpYA6w0t1PDTuPFIH0NFg5BxZNgzLloM0/oGEnKKXpk8O25LdNvL14Fb9u3MGJB/6Nn+e8y3WDB7Fp0yZOPPFEjjzyyKQp7r5fvZX3Ulex9Pct/F+bfTisRS1qVS4fdqyEEvcCL68PeDMrDzwBdCIyJcN57v5TvDOJiIhI3A0EUolcty8lwYpZ8MRp4B55PGscXDodGncON1cJ9+2qLZw//gs270gnfctaxt74MDu+n8UhhxzCxIkTOfjgg8OOGLMV67fTc9IsftkYGQfqpa9Wcv3f9+OKbi01N1+UPTqkYmalzGxPP6izPuBz0hvY4O6tgDHAXXu4bxEREUkwZtYIOAWYEHYWKSKZmZGCLqu4A8hMh4VTw8skAHy9YiObd6QDsPbVu9n503yan3IFb7z7YVIVdwCpv23+o7jL8uD737Nyw46QEiWmfAs8M3vGzKoFUyMsApaYWSwjbMXyAX8GkHUx94vAcabyW0REJNndB1wPZOa00Mz6mdkcM5uzZs2aIg0mcbQ7hz+y0/WHd9hW/vwTmbu2AVDrhCup3+tB6h1+FqWS8NTZzOgDCIGMTCcjh/aSLJZTNNu4+2YzuwiYDgwF5gL3xLDtfUQ+4KvmsrwhsALA3dPNbBNQG/jTBOtm1g/oB9CkSZMYnjZvJ550Ejt36AMnS7du3cKOkBAqVKzIjOnTQ81w7ln/ZPW6DaFmSCR6b0bUq12TF6ZOCzuGSEzM7FRgtbvPNbNuOa3j7uOB8QApKSn6y6w4KFUKDr0cfnjvf21m0Pbc8DKVcBkZGdx3333cfPMwKhx0PNWP60e5us0A6H9MS2pXSb7r1vbbpyo1KpVl4/bdf7T17NqMhjUqhpgq8cRS4JU1s7LAP4Cx7r7bzPL9MI7lAz5Whf1FsHPHDrYc0mtvdyPFzexJYSdg9boNPHHsurBjSILp8X7YCaSkMbMKwKnAkUADItMkLQLecPfF+WzeFTjdzE4mMn9uNTN7yt27xzOzJIBmXeHCF+CLh6F0OehyJTQ8JOxUJdKiRYvo1asXs2fP5rTTTqP/zXcwfVkaKzbsoPthTTh637phRyyQ5nWr8HSfQ3lm1s8s/nUzZ3VqyPEH7EOZ0snXGxlPsRR4jwA/AV8DH5lZU2BzDNvF8gG/EmgM/GJmZYDqRAZbERERkRCY2S1EiruZwCxgNZHv8X2BfwfF37XuviCn7d39RuDGYF/dgCEq7kqIcpVh379Dy+Mij0trsPYwPPPMM/Ts2ZMaNWrw3HPPce6552JmHJ/ipHsm5UqXDjviXjmwQXVu+8dB7M7IpFyZ5H4t8RLLPHgPAA9ENS03s3ynto/xA/5V4BLgc+Bs4H13nUQrIiISoi/dfUQuy0abWT1g76+XkOJLhV0oMjIyKF26NIcffjjdu3fn7rvvpk6dOn8sL1XKKEfxKIjMTMVdHvL9H2hmNYAeQLNs619dkCc0s1uBOe7+KjAReNLMvgfWA+cXZJ8iIiJSONz9jXyWrybSqxfLvmYS6QkUkTjZvn07w4YN49tvv+XVV1+lWbNmTJoU/mUnEp5YDrG8CXwBLCSX0bDyE/0B7+7Do9p3AucUZJ8iIiJStMxsvLv3CzuHiER88MEH9OnTh2XLlnH55Zeze/duypUrF3YsCVksBV4Fdx8c9yQiIiISOjOrldsi4OSizCIiOdu8eTNDhgzh0UcfpVWrVsycOZOjjz467FiSIGIp8J40s77A68CurEZ3Xx+3VCIiIhKWNcByIgVdFg8e1wslkYj8SWZmJtOnT+e6665j5MiRVKpUKexIkkBiKfDSiMx59y8iH/AEP1vEK5SIiIiEZhlwnLv/nH2Bma0IIY+IAKtXr2b06NGMGjWKGjVq8M0331C5cuWwY0kCimXSiGuBVu7ezN2bBzcVdyIiIsXTfUDNXJbdXYQ5RARwd55++mnatGnDmDFjmDVrFoCKO8lVLAXe98D2eAcRERGR8Ln7Q+7+dS7LHizqPCIl2YoVKzj11FPp3r07rVu35quvvuKII44IO5YkuFhO0dwGzDezD/jzNXgFmiZBREREEpeZHeHun+SxvBrQxN0XFWEskRLpggsu4KuvvuK+++5jwIABlE7yScqlaMRS4L0c3ERERKT4O8vM7gZmAHOJDLpSAWgFHAM0JXL5hojEwXfffUe9evWoXr0648aNo1KlSrRooaujJHb5Fnju/riZlQP2DZqWuvvu+MYSERGRMLj7NcFUCWcRmau2PrADSAUeyat3T0QKLj09nTFjxjB8+HD69evH/fffz0EHHRR2LElC+RZ4ZtYNeBz4icgQyY3N7BJ3/yiuyURERCQUwVRIjwY3EYmzBQsW0Lt3b+bMmcM//vEPbrjhhrAjSRKL5RTN/wAnuPtSADPbF3gW6BTPYCIiIiIixd3TTz9Nz549qVWrFi+88AJnn302Zpb/hiK5iGUUzbJZxR2Au38LlI1fJBERERGR4i0jIwOArl270rNnT5YsWcI555yj4k72WiwF3hwzm2Bm3YLbo8CceAcTERERESlutm7dyqBBgzjjjDNwd5o1a8ajjz5K7dq1w44mxUQsp2heAfQHsqZF+Bh4KG6JREREJDRmdmZey939paLKIlLcvPPOO/Tr14+ffvqJK6+8kt27d1OuXLmwY0kxE0uBd7m7jwZGZzWY2UDg/rilEhERkbCclu3+a1GPHVCBJ7KHNm3axODBg5k0aRL77rsvH330EUceeWTYsaSYiqXAu4S/FnM9c2gTERGRJOful2bdN7Ovoh+LSMG4O++++y5Dhw5lxIgRVKhQIexIUozlWuCZ2QXAhUBzM3s1alFVYH28g4mIiEjoPOwAIslq1apV/Oc//+G2226jRo0apKamUqlSpbBjSQmQVw/eZ8BvQB0iUyVk2QIsiGcoEREREZFk5O489dRTDBo0iK1bt3L66adzxBFHqLiTIpNrgefuy4HlQJeiiyMiIiJhMrPX+F/PXYtsZ/Hg7qcXfSqR5PDzzz9z2WWXMWPGDA4//HAmTpzI/vvvH3YsKWHyvQbPzA4DHgQOAMoBpYFt7l4tztlERESk6N0bdf8/ua4lIn9x4YUXMn/+fB544AH69+9PqVKxzEgmUrhiGWRlLHA+MAVIAXoA+8YzlIiIiITD3T/M3mZmNYHG7q5LNESy+fbbb6lXrx41atTgkUceoXLlyjRr1izsWFKCxXRYwd2/B0q7e4a7PwacGN9YIiIiEiYzm2lm1cysFjAPeNTMRue3nUhJkZ6ezr///W/atm3L8OHDATjwwANV3EnoYunB225m5YD5ZnY3kYFX1N8sIiJSvFV3981m1gd4wt1HmJl68ESA+fPn07t3b+bNm8dZZ53FTTfdFHYkkT/EUqhdHKw3ANgGNAbOimcoERERCV0ZM6sPnAu8HnYYkUTx5JNPkpKSwsqVK3nxxRd58cUX+dvf/hZ2LJE/5NuDF4ymCbATuCW+cURERCRB3Aq8BXzi7rPNrAXwXX4bmVkF4COgPJG/M1509xFxTSoSB3N/Ws/S1VtIz3Ba16vCIU1rUKZMGY466ij69OnDHXfcQa1atcKOGZOFv2wk9bctbN+dQcu6lTmkaS0qlCsddiyJk1hO0SyQWD7gzawncA+wMmga6+4T4pVJREREYuPuU4gMsJb1eBmxncGzCzjW3beaWVngEzOb7u5fxCmqSKGbtWwdVz37Fau37CIzbQdbP3mSfStu4/OZ79C0aVPGjRsXdsSYzV+xgWtfWMAPa7YCUKaU8dCFHfj7QfVDTibxErcCj9g/4J939wFxzCEiIiJ7yMzqAn2BZkT9veDuvfLazt0d2Bo8LBvcPPctRBLPp9+vZfWWXexYNpd1bz1ExuY1bDv+XDZu2UbNalXCjrdHFq/c/EdxB5Ce6dz/3vcc1LA6DWtq8vXiKM8Cz8xKA3e5+5A93bE+4EVERJLaK8DHwLtAxp5sGPz9MBdoBTzk7rOyLe8H9ANo0qRJoYQVKUzLfl3N2jfGsG3Re5Sp1Yh9LrqLJp0PY3dc+0biY8P2tL+0/bZpB1t3pYeQRopCnu9Sd88wsyMKuvP8PuADZ5nZUcC3wDXuviKH/eiLQEREpGhVcvcbCrKhu2cA7c2sBjDNzA5y90VRy8cD4wFSUlJ08FcSTpcWtRj380KqdTmPGoefh5Upx6lt61OvWoWwo+2x/f9W7S9tp7VrQPNalUNII0UhllE0vzKzV83sYjM7M+sWy86DefPaA42AzmZ2ULZVXgOauXtb4B3g8Vz2M97dU9w9pW7durE8tYiIiOyd183s5L3ZgbtvBD5A8+dKEvj9998ZMmQIaWlpHH5AU+5/8QNantSbKpUqctlRLTiydZ2wIxZIxyY1uPvstjSoXoHyZUpxXkpjzurYkHIaZKXYiqWfuQKwDjg2qs2Bl2J9EnffaGZZH/DRR/DWRa02Abg71n2KiIhIXA0EbjKzXcBuwIhcgfHX7oAowbV7u4Pv/orA8cBdcU8rUkDuzuOPP84111zDjh07+Oc//0nXrl3pf3wbjj2oIZmZsN8+lSlTJvlOzwSoVaU856Y0pmOTGuzanUnzOpWoVL5s2LEkjmKZJuHSguw4lg94M6vv7r8FD08HUgvyXCIiIlK43L1qATetDzweXKZRCnjB3TWPniSkn376iX79+vHOO+9wxBFHMGHCBPbbb78/lh9Qv3qI6QpXq3oF/S8tySbfAi+Y7qA3cCCR3jwg/1G0yOUD3sxuBea4+6vA1WZ2OpAOrAd6FuhViIiISKEws47ZmhxYm9M18jlx9wVAh0IPJhIH3bt35+uvv+ahhx7i8ssvp1SpWK5eEklssfQ1Pwl8A/ydyKSnFxFDT1tuH/DuPjzq/o3AjbGGFRERkbj7Tw5ttcysHHCBu88v4jwihSo1NZX69etTo0YNxo8fT5UqVTSInxQrsRymaOXuw4Bt7v44cApwaHxjiYiISBjc/Zgcbu2Ai4EHws4nUlC7d+/m9ttvp3379owYMQKANm3aqLiTYieWHrzdwc+NwSiYvwP14hdJREREEo27zzGz5JrhWSQwb948evXqxddff825557LTTfdFHYkkbiJpQdvvJnVBIYBrwJL0GiXIiIiJYqZ7UPkejyRpPLEE0/QuXNnVq1axbRp03j++efZZ599wo4lEjexjKI5Ibj7IdAivnFEREQkTGb2IH8t5GoBhxOZOkEkKaSnp1OmTBm6detGv379uP3226lZs2bYsUTiLtcCz8wG57Whu48u/DgiIiISsjnZHjuR+XAHu/vqEPKI7JHNmzdz4403smzZMt58802aNGnCf//737BjiRSZvHrwNFmGiIhICRMMqCaSlKZPn85ll13GL7/8wsCBA9m9ezflypULO5ZIkcq1wHP3W4oyiIiIiITPzFoDNwEbgNHAo8CRwA9AH3efHWI8kRxt2LCBgQMH8uSTT9KmTRs+/fRTunTpEnYskVDkO8iKmTUys2lmtjq4TTWzRkURTkRERIrcY8DnwK/ALGASUAcYAowNMZdIrkqVKsUnn3zC8OHDmTdvnoo7KdFiGUXzMSKjZzYIbq8FbSIiIlL8VHH38e5+L7DD3ae4+053fwcoH3Y4kSy//vor11xzDWlpaVSvXp0lS5Zwyy23UL683qZSssVS4NV198fcPT24TQbqxjmXiIiIhCMz6v7mPJaJhMLdmThxIm3atGHcuHHMmRMZF6hChQohJxNJDLEUeOvMrLuZlQ5u3YmMpiUiIiLFz/5mtsDMFkbdz3q8X9jhpGRbtmwZxx9/PH369KF9+/YsWLCAww8/POxYIgkl33nwgF7Ag8CY4PGnwKVxSyQiIiJhOiDsACK56dGjBwsWLGDcuHH07duXUqVi6asQKVlimeh8OXB6EWQRERGRkAXf+yIJY8mSJdSvX5+aNWvy6KOPUqVKFRo3bhx2LJGEFcsomi3M7DUzWxOMovmKmbUoinAiIiIiUjKlpaUxatQoOnTowIgRIwA44IADVNyJ5COWfu1ngBeA+kRG0ZwCPBvPUCIiIiJScs2ePZuUlBSGDx/OmWeeybBhw8KOJJI0YinwKrn7k1GjaD4FaJgiERERESl0kydP5rDDDmPdunW88sorPPvss9StqwHcRWIVS4E33cyGmlkzM2tqZtcDb5pZLTOrFe+AIiIiUvTMrKuZvWNm35rZMjP70cyWhZ1Liq/du3cDcOyxx3LFFVewZMkSTj9dw0CI7KlYRtE8N/h5Wbb28wEHdD2eiIhI8TMRuAaYC2SEnEWKsU2bNnHDDTfw448/MmPGDJo0acLYsWPDjiWStGIZRbN5UQQRERGRhLLJ3aeHHUKKtzfeeIPLLruM3377jWuuuYb09HTKli0bdiyRpBZLD56IiIiUPB+Y2T3AS8CurEZ3nxdeJCku1q9fz1VXXcUzzzzDQQcdxEsvvUTnzp3DjiVSLKjAExERkZwcGvxMiWpz4NgQskgxU7p0ab744gtGjhzJjTfeSLly5cKOJFJsqMATERGRv3D3Y8LOIMXLypUrufvuu7nnnnuoXr06S5YsoXz58mHHEil2VOCJiIjIX5jZ4ByaNwFz3X1+EceRJObuTJgwgSFDhrB7927OP/98unTpouJOJE5imSbhL8zsq8IOIiIiIgklBbgcaBjcLgNOBB4NpkzKkZk1NrMPzGyJmS02s4FFE1cS0Q8//MBxxx1Hv3796NSpEwsXLqRLly5hxxIp1gpU4Ll7h/zWMbMKZvalmX0dfMDfksM65c3seTP73sxmmVmzguQRERGRQtcI6Oju17r7tUAnoB5wFNAzj+3SgWvdvQ1wGNDfzNrEO6wkpksuuYS5c+cyfvx43nvvPVq2bBl2JJFiL98Cz8zuiqUtB7uAY929HdAeONHMDsu2Tm9gg7u3AsYAsexXRERE4q8eUaNnAruBfdx9R7b2P3H337JG2nT3LUAqkR5AKSEWLlzIhg0bAJgwYQKLFy+mb9++mFnIyURKhlh68I7Poe2k/DbyiK3Bw7LBzbOtdgbweHD/ReA40/9+ERGRRPA0MMvMRpjZCOBT4BkzqwwsiWUHwZk5HYBZ2dr7mdkcM5uzZs2aQo4tYdm1axcjRoygY8eOjBgxAoD999+fRo0ahZxMpGTJdZAVM7sCuBJoYWYLohZVJfIhny8zKw3MBVoBD7n7rGyrNARWALh7upltAmoDa7Ptpx/QD6BJkyaxPHWeatauA7Mn7fV+pHipWbtO2BGoVLECPd6vHXYMSTCVKlYIO4KUQO4+ysymA12DpsvdfU5w/6L8tjezKsBUYJC7b8627/HAeICUlJTsB38lCc2aNYvevXuzePFiunfvzvDhw8OOJFJi5TWK5jPAdOBOYGhU+xZ3Xx/Lzt09A2hvZjWAaWZ2kLsv2tOQhf1FMG3qi3u7i2KjW7duzJw5M+wYEnhz+oywI4hICWdm1dx9s5nVApYFt6xltWL5G8DMyhIp7p5295fil1YSweTJk+nduzcNGjTg9ddf55RTTgk7kkiJlmuB5+6biAyHfAGAmdUDKgBVzKyKu/8c65O4+0Yz+4DI6FvRBd5KoDHwi5mVAaoD6/b4VYiIiEhheQY4lcgZONEHVS143CKvjYNLLSYCqe4+Ol4hJXy7d++mbNmyHHfccQwYMIBRo0ZRrVq1sGOJlHixDLJympl9B/wIfAj8RKRnL7/t6gY9d5hZRSLX8n2TbbVXgUuC+2cD77u7TtUQEREJibufGvxs7u4tom7N3T3P4i7QFbgYONbM5ge3k+MaWorUxo0b6du3L6eccgruTuPGjbn//vtV3IkkiFgGWbmNyDDH37p7c+A44IsYtqsPfBBcvzcbeMfdXzezW83s9GCdiUBtM/seGMyfTwUVERGRkJhZ12BAFcysu5mNNrN8L4R390/c3dy9rbu3D25vxj+xFIVXX32VAw88kEmTJtG+fXvS09PDjiQi2eR1DV6W3e6+zsxKmVkpd//AzO7LbyN3X0Bk5Kzs7cOj7u8EztmTwCIiIlIkHgbamVk74FpgAvAkcHSoqSQU69ev58orr+T555/n4IMP5pVXXiElJSXsWCKSg1h68DYGI2F9BDxtZvcD2+IbS0REREKWHlw2cQYw1t0fIjKStpRAZcqUYc6cOYwaNYo5c+aouBNJYLEUeGcA24FrgBnAD8Bp8QwlIiIiodtiZjcSuZ7uDTMrRWROWykhVqxYwYABA9i1axfVqlVj8eLF3HzzzZQrVy7saCKSh1gKPCAyTx3wOZFBVjbnvbaIiIgkufOAXUAvd/8daATcE24kKQqZmZk8/PDDHHjggTz22GPMmzcPgPLly4ecTERiEUuB9xFQwcwaAm8TOZI3OZ6hREREJFxBUTcVyPqrfi0wLbxEUhS+++47jjnmGK688koOPfRQFi1aRJcuXcKOJSJ7IJYCz9x9O3Am8F93Pwc4ML6xREREJExm1hd4EXgkaGoIvBxaICkSPXv2ZMGCBUyaNIm3336b5s2bhx1JRPZQLKNompl1AS4CegdtpeMXSURERBJAf6AzMAvA3b8zs3rhRpJ4WLBgAY0aNaJWrVpMmjSJatWqUb9+/bBjiUgBxdKDNxC4EZjm7ovNrAXwQXxjiYiISMh2uXta1gMzKwN4iHmkkO3atYthw4bRqVMnRo4cCcB+++2n4k4kyeXbg+fuHxG5Di/r8TLg6niGEhERkdB9aGY3ARXN7HjgSuC1kDNJIfn888/p3bs3qamp9OjRgxEjRoQdSUQKSb4FnpntCwwBmkWv7+7Hxi+WiIiIhGwokUszFgKXAW8SmexcktykSZPo06cPjRs3Zvr06Zx44olhRxKRQhTLNXhTgHFEPtQz4htHREREEoG7ZwKPBjcpBtLS0ihXrhzHH388AwcO5NZbb6VqVc1dL1LcxFLgpbv7w3FPIiIiIqEzs4Xkca2du7ctwjhSCDZs2MCQIUNYvnw577zzDo0bN2bMmDFhxxKROImlwHvNzK4kMvfNrqxGd18ft1QiIiISllODn/2Dn08GP7ujQVaSzrRp07jyyitZs2YN119/Penp6ZQtWzbsWCISR7EUeJcEP6+LanOgReHHERERkTC5+3IAMzve3TtELbrBzOYRuTZPEty6deu4/PLLefHFF2nfvj1vvPEGHTt2DDuWiBSBWEbR1AyXIiIiJY+ZWVd3/zR4cDixTa8kCaBs2bJ8/fXX3HHHHQwZMkS9diIlSK4Fnpmdma3JgbXAfHffEtdUIiIiErbewCQzqw4YsAHoFW4kycvy5cu5++67GT16NNWqVWPRokWUK1cu7FgiUsTy6sE7LYe2WkBbM+vt7u/HKZOIiIiEzN3nAu2CAg933xRyJMlFZmYmDz/8MEOHDsXdufjiiznssMNU3ImUULkWeO5+aU7tZtYUeAE4NF6hREREJDG4+yYze53/Db4iCWTp0qX06dOHTz75hBNOOIFHHnmEZs2ahR1LREIUyyArf+Luy81MJ3KLiIiUHA3DDiA56927N0uWLGHy5Mn06NEDMws7koiEbI8LPDPbj6jpEkRERKTY+yrsAPI/X331FU2bNqVWrVpMmjSJatWq8be//S3sWCKSIHIdDcvMXjOzV7PdPgHeBAYXXUQREREpamY2MOu+u/fK3iZFb+fOndx0000ccsghjBw5EoB9991XxZ2I/ElePXj3ZnvswDrgO3dPi18kERERSQCXAPdna+uZQ5sUgU8//ZTevXuzdOlSLr30Um655ZawI4lIgsprkJUPizKIiIiIhM/MLgAuBJqb2atRi6oB68NJVbJNnDiRvn370qRJE9566y1OOOGEsCOJSALb42vwREREpFj7DPgNqAP8J6p9C7AglEQl1K5duyhfvjwnnngigwcPZuTIkVSpUiXsWCKS4HK9Bk9ERERKHndf7u4zgf8DPg7O6PkNaERkwvM8mdkkM1ttZovim7T42JGWwXertrB87TYyM53169fTs2dPTj75ZNydhg0bcu+996q4E5GYxK0Hz8waA08A+xC5fm+8u9+fbZ1uwCvAj0HTS+5+a7wyiYiISMw+Ao40s5rA28Bs4Dzgony2mwyMJfI3gOTjp3Xb+Peb3zBj8e9UKFuKo8st4+Wxo1i3bi1Dhw4lPT2dsmU1O5WIxC7XAs/MFhIpzHLk7m3z2Xc6cK27zzOzqsBcM3vH3ZdkW+9jd9fkqSIiIonF3H27mfUG/uvud5vZ/Pw2cvePzKxZ3NMVA5mZztNfLGfG4t/J2L6JFW89xPhvP6N1m4N5660ZtG/fPuyIIpKE8urByyq6+gc/nwx+5nfkDgB3/43IKR24+xYzSyUyUWr2Ak9EREQSj5lZFyLf+72DttIh5il2NmxP47WvfwPASpclbe1yahzdkytvup727Q8IOZ2IJKu8RtFcDmBmx7t7h6hFQ81sHjA01icJjuR1AGblsLiLmX0N/AoMcffFOWzfD+gH0KRJk1ifVkRERApuEHAjMM3dF5tZC+CDwtixvtcj1v72CxvfeQjv1INS5SvRoNdDWOkyNK9XLexoIpLEYhlkxcysa9SDw2PcLmv9KsBUYJC7b862eB7Q1N3bAQ8CL+e0D3cf7+4p7p5St27dWJ9aRERECsjdP3T304GHzKyKuy9z96sLad8l+ns9IyODBx54gE4d2rFi9juU3bgcACtdhpSmNUlpWjPkhCKSzGIZZKU3MMnMqgePNwK9Ytm5mZUlUtw97e4vZV8eXfC5+5tm9l8zq+Pua2PZv4iIiMSHmR1MZKCUWpGHtgbokdOZNhK71NRUevfuzeeff85JJ53EuHHjyKhYi+9Xb6ViudLs97eq1K1aIeyYIpLE8i3w3H0u0C6rwHP3TbHs2MwMmAikuvvoXNb5G7DK3d3MOhPpGVwXa3gRERGJm0eAwe7+Afwx8vWjwOF5bWRmzwLdgDpm9gswwt0nxjVpknB3+vbty9KlS3nyySe56KKLiPy5BM3ragoEESkc+RZ4ZrYPcAfQwN1PMrM2QJcYPqy7AhcDC6NG3boJaALg7uOAs4ErzCwd2AGc7+65jtwpIiIiRaZyVnEH4O4zzaxyfhu5+wXxjZV85s2bR9OmTalduzaPPfYY1atXp169emHHEpFiKpZr6SYDbwENgsffErnwOk/u/om7m7u3dff2we1Ndx8XFHe4+1h3P9Dd27n7Ye7+WQFfh4iIiBSuZWY2zMyaBbebgWVhh0omO3bsYOjQoXTu3JlbbrkFgNatW6u4E5G4iqXAq+PuLwCZAO6eDmTENZWIiIiErRdQF3iJyPX0dYjxGnyBjz76iHbt2nHXXXfRs2dPbr311rAjiUgJEcsgK9vMrDbBpOdmdhgQ03V4IiIiklzMrAJwOdAKWAhc6+67w02VXCZMmEDfvn1p3rw57777Lscdd1zYkUSkBImlB28w8CrQ0sw+JTKi1lVxTSUiIiJheRxIIVLcnQTcE26c5LFz504ATjrpJK6//noWLlyo4k5Eilwso2jOM7Ojgf0AA5bqSJ6IiEix1cbdDwYws4nAlyHnSXhr167lmmuuYeXKlbz33ns0bNiQu+66K+xYIlJC5dqDZ2bHBj/PBE4nUuDtC5wWtImIiEjx88dB3OC6e8mFu/PCCy/Qpk0bnnvuOY488kgyMjRMgYiEK68evKOB94HTcljmRC66FhERkeKlnZltDu4bUDF4bIC7e7XwoiWOtWvX0qdPH1555RVSUlJ49913adu2bdixRERyL/DcfYSZlQKmB6NoioiISDHn7qXDzpAMKlSowNKlS7nnnnsYNGgQZcrEMm6diEj85TnIirtnAtcXURYRERGRhLVs2TL69u3Lzp07qVKlCgsXLmTIkCEq7kQkocQyiua7ZjbEzBqbWa2sW9yTiYiIiCSAjIwM7rvvPg4++GCef/55FixYAKDCTkQSUiyfTOcFP/tHtTnQovDjiIiIiCSOxYsX07t3b2bNmsUpp5zCuHHjaNSoUdixRERyFcs0Cc2LIoiIiIhIInF3LrvsMn744QeeeeYZzj//fMws7FgiInnKt8Azsx45tbv7E4UfR0RERCRcs2fPpkWLFtSuXZvJkydTvXp16tatG3YsEZGYxHIN3iFRtyOBkUTmxRMREREpNrZv386QIUM47LDDuOWWWwBo1aqVijsRSSqxnKJ5VfRjM6sBPBevQCIiIiJFbebMmfTp04cffviByy67jFGjRoUdSUSkQGLpwctuG6Dr8kRERKRYGD9+PMcccwwA77//PuPGjaN69eohpxIRKZhYrsF7jciomRApCNsAmvhcREREktqOHTuoWLEip556KjfeeCM333wzlSpVCjuWiMheiWWahHuj7qcDy939lzjlEREREYmrNWvWMGjQIH799Vfee+89GjRowB133BF2LBGRQpHvKZru/mHWDVgKrIx/LBEREZHC5e48++yztGnThilTptCtWzcyMzPDjiUiUqhyLfDM7DAzm2lmL5lZBzNbBCwCVpnZiUUXUURERGTvrFmzhtNPP50LL7yQFi1aMG/ePEaMGEGZMrGczCQikjzy+lQbC9wEVAfeB05y9y/MbH/gWWBGEeQTERER2WsVK1bkhx9+YPTo0Vx99dWULl067EgiInGR1ymaZdz9bXefAvzu7l8AuPs3RRNNREREpOC+//57evXqxc6dO6lSpQoLFizgmmuuUXEnIsVaXgVe9EnpO7Itc0REREQSUHp6Ovfeey8HH3wwL730EgsXLgTQ6ZgiUiLk9UnXzsw2AwZUDO4TPK4Q92QiIiIie2jhwoX07t2b2bNnc8YZZ/Df//6XBg0ahB1LRKTI5FrgubvOXxAREZGk4e5cccUV/PTTTzz//POcc845mFnYsWKyftsuypUuRZUKZcOOIiJJLt9pEgrKzBqb2QdmtsTMFpvZwBzWMTN7wMy+N7MFZtYxXnlERESkaJjZiWa2NPh+Hxrv55s1axZr167FzHj88cdZsmQJ5557blIUd2u27GTSJz9y+thPueDRWcxcupq0dE3dICIFF7cCj8ik6Ne6exvgMKC/mbXJts5JQOvg1g94OI55REREJM7MrDTwEJHv+DbABTl8/xeKbdu2MXjwYLp06cKoUaMAaNmyJXXq1InH08XFa1//xq2vL+GXDTtYuHITl06ezYJfNoYdS0SSWNwKPHf/zd3nBfe3AKlAw2yrnQE84RFfADXMrH68MomIiEjcdQa+d/dl7p4GPEfk+75Qvf/++7Rt25YxY8Zw+eWX/1HgJZP129J47LMf/9TmDnOXbwgpkYgUB0UynJSZNQM6ALOyLWoIrIh6/EvQ9lu27fsR6eGjSZMmcctZlLp16xZ2hD8kQpaZM2eGHUFERApHTt/th0avsLff64888giXX345rVq1YubMmRx99NF7ETc85coYtSqVY8X6Pw9WXrWCRvsUkYKL+yeImVUBpgKD3H1zfuvnxN3HA+MBUlJSisUUDSpoRESkpCro9/r27dupVKkSp512GitWrOBf//oXFStWjFvOeKtSvizXnrAfPR/7kszgt1CnSjk6N68VbjARSWpxLfDMrCyR4u5pd38ph1VWAo2jHjcK2kRERCQ5Ffp3+6pVq7j66qtZtWoV77//Pg0aNOC2227bq5CJokvL2ky5/HDm/byeahXK0qlpTVrVqxp2LBFJYnEr8CwydNVEINXdR+ey2qvAADN7jsjpG5vc/bdc1hUREZHENxtobWbNiRR25wMXFmRH7s7TTz/NwIED2bp1K8OHDyczM5NSpeI5RlzRKlu6FJ2a1qRT05phRxGRYiKePXhdgYuBhWY2P2i7CWgC4O7jgDeBk4Hvge3ApXHMIyIiInHm7ulmNgB4CygNTHL3xXu6n9WrV9OzZ0+mT59Oly5dmDhxIgcccECh5xURKW7iVuC5+ydAnhPQuLsD/eOVQURERIqeu79J5CBugVWqVIkVK1Zw//33079/f0qXLl1I6UREirfic46DiIiIJLVvv/2WSy+9lJ07d1KlShXmz5/P1VdfreJORGQPqMATERGRUKWnp3P33XfTrl07Xn75ZRYuXAigwk5EpAA00YqIiIiEZseOHRx66KHMmzePf/7znzz00EPUr18/7FgiIklLBZ6IiIiEZvny5VSuXJkpU6Zw1llnERmEW0RECsoi45wkDzNbAywPO0cxUgdYG3YIkRzovVm4mrp73bBDiGRXCN/rxemzQq8lMem1JKaS/lpy/V5PugJPCpeZzXH3lLBziGSn96aIxKI4fVbotSQmvZbEpNeSOw2yIiIiIiIiUkyowBMRERERESkmVODJ+LADiORC700RiUVx+qzQa0lMei2JSa8lF7oGT0REREREpJhQD56IiIiIiEgxoQJPRERERESkmFCBl6DMLMPM5pvZIjObYmaVCnHfWwu43QQza1NYOSS57O170syamdmFe7DuogLmfNPMahRkWxFJHmZ2opktNbPvzWxo2Hn2hplNMrPVBf3cSyRm1tjMPjCzJWa22MwGhp2poMysgpl9aWZfB6/llrAz7S0zK21mX5nZ62Fn2Rtm9pOZLQz+LpkTdp69YWY1zOxFM/vGzFLNrMve7lMFXuLa4e7t3f0gIA24PHqhmZUp6kDu3sfdlxT180rCyPM9GYNmQEwF3t5w95PdfWO8n0dEwmNmpYGHgJOANsAFSX4AcjJwYtghCkk6cK27twEOA/on8b/NLuBYd28HtAdONLPDwo201wYCqWGHKCTHBH+XJPtcePcDM9x9f6AdhfDvowIvOXwMtDKzbmb2sZm9CiwJjsLcY2azzWyBmV2W08Zm1tzMPg+OdNyWbdl1UdvfErRVNrM3giNWi8zsvKB9ppmlBPd7m9m3wZGtR81sbNA+2cweMLPPzGyZmZ0dz1+MhCbrPVnLzF4O3j9fmFlbADM7OjiqNj84UlgV+DdwZNB2TfYdmlmn4D33NdA/qj3H97mZ1Tezj6J6FY8M2n8yszrB/WHBEf5PzOxZMxsStM80s7uC9++3WduKSNLoDHzv7svcPQ14Djgj5EwF5u4fAevDzlEY3P03d58X3N9C5I/VhuGmKhiPyDrrqWxwS9rRCc2sEXAKMCHsLBJhZtWBo4CJAO6eVhgHqVXgJbigp+4kYGHQ1BEY6O77Ar2BTe5+CHAI0NfMmuewm/uBh939YOC3qH2fALQm8kXZHuhkZkcROYr4q7u3C3prZmTL1AAYRuTIXFdg/2zPVx84AjiVyB/1Uoxke0/eAnzl7m2Bm4AngtWGAP3dvT1wJLADGAp8HBxtG5PDrh8DrgqOlEbL7X1+IfBW8BztgPnZch4CnBUsOwnIfoSvjLt3BgYBI/bgVyAi4WsIrIh6/AtJWkQUZ2bWDOgAzAo5SoEFBxnnA6uBd9w9aV8LcB9wPZAZco7C4MDbZjbXzPqFHWYvNAfWAI8FB8QnmFnlvd2pCrzEVTH4QJkD/ExQ2QNfuvuPwf0TgB7BerOA2kQKtuy6As8G95+Maj8huH0FzCNSqLUm8of78UEPx5Huvinb/joDH7r7enffDUzJtvxld88MTufcZw9esyS2nN6TRxC8p9z9faC2mVUDPgVGm9nVQA13T89rxxa5Zq5GcBQb/vo+zel9Phu41MxGAgcHR4qjdQVecfedwbLXsi1/Kfg5l8jpoyIiUkjMrAowFRjk7pvDzlNQ7p4RHEhsBHQ2s4NCjlQgZnYqsNrd54adpZAc4e4diRzA7R90UCSjMkQ6bx529w7ANiIHxPd6p5KYdgQfKH8wM4j8w//RRKTH461s691OpAueqH3kdEqBAXe6+yN/WWDWETgZuM3M3nP3W/cg+65szyHFQ27vyb9w93+b2RtE3kOfmtnfs69jZo8RObL7K3lfm5fj+zzYx1FE3uuTzWy0uz/xl61zl/U+zUCfhSLJZiXQOOpxo6BNEoCZlSVS3D3t7i/lt34ycPeNZvYBkbOcknEwnK7A6WZ2MlABqGZmT7l795BzFYi7rwx+rjazaUQ6Hz7Ke6uE9AvwS1TP8IsUQoGnHrzk9hZwRfBBipnta2aV3f1fwWlw7YP1PgXOD+5flG37XsFRNsysoZnVC07B3O7uTwH3EDmyEG02cLSZ1QxO1zsrLq9OksHHBO8pM+sGrHX3zWbW0t0XuvtdRN4v+wNbgKpZG7r7pcH7NGtQlI1mdkSwOPv79C/vczNrCqxy90eJXE+Q/X36KXCaRUZBq0LklGERKR5mA60tco15OSLfca+GnEkAixz5mwikuvvosPPsDTOrG5xhgplVBI4Hvgk1VAG5+43u3sjdmxH5//J+shZ3wd8AVbPuEznTJxmLbtz9d2CFme0XNB0H7PWAhjpqndwmEDm1bF7wgboG+EcO6w0EnjGzG4BXshrd/W0zOwD4POiJ2Qp0B1oB95hZJrAbuCJ6Z+6+0szuAL4kclH4N0D20zilZBgJTDKzBcB24JKgfZCZHUPkPP/FwPTgfkYwiMrkHK7DuzTYlwNvR7Xn9j7vBlxnZruJvHd7RO/M3WdbZECiBcAqIqce630qUgy4e7qZDSByAKg0MMndF4ccq8DM7Fkin2l1zOwXYIS7T8x7q4TVFbgYWBicWg9wk7u/GV6kAqsPPG6RUVtLAS+4e1JPL1BM7ANMC/52LQM84+4z8t4koV0FPB0crFpG5O+hvWLuSTsYkITIzKq4+9agB28akS/XaWHnEokW9T6tROTUjX5Zo7uJiIiIFEfqwZOCGmlm/0fkPO63gZfDjSOSo/EWmX+pAvC4ijsREREp7tSDJyIiIiIiUkxokBUREREREZFiQgWeiIiIiIhIMaECT0REREREpJhQgSciIiJSAplZhpnNN7NFZjYlGHG4sPa9tYDbTQgGxyqMDFmv72szm2dmhwft3czs9WzrTjazswvwHM3MbFG2tpFmNiSX9QeZWY/g/jlmttjMMs0sJWqdg81sci7b9zSzNWY2Iaqts5l9ZGZLzeyr4HdYaP+WUc/bIOrx02a2viC/M4k/FXgiIiIiJdMOd2/v7gcBacDl0QuDqZCKlLv3cfe9nug5kPX62gE3AncW0n4LJPh99gKeCZoWAWcSmcbnD+6+EGhkZk1y2dXz7t4n2Oc+wBTgBnffz907ADOAqoUcvyfwR4Hn7hcBrxbyc0ghUYEnIiIiIh8DrYLerY/N7FVgiZmVNrN7zGy2mS0ws8ty2tjMmpvZ52a20Mxuy7bsuqjtbwnaKpvZG0Hv2iIzOy9on5nVm2Vmvc3sWzP70sweNbOxQftkM3vAzD4zs2Ux9iJVAzbE8osws5/M7Jag12+hme0ftB8d9AjOD3rK9rSIOhaY5+7pAO6e6u5Lc1n3NeD8GPbZn8g0QJ9nNbj7i+6+ysxqmdnLwe/9CzNrG7yOP/UwBr//ZsEtNfhdLzazt82sYvD7TSEyGfd8M6u4h69bipgKPBEREZESLOhZOglYGDR1BAa6+75Ab2CTux8CHAL0NbPmOezmfuBhdz8Y+C1q3ycArYHOQHugk5kdBZwI/Oru7YIexBnZMjUAhgGHAV2B/bM9X33gCOBU4N+5vLSKQUHyDTABGJXf7yLKWnfvCDwMZBVDQ4D+7t4eOBLYEbS3jCr85pOtJzRKV2BujM8/J3iO/ByUxz5vAb5y97bATcATMeyvNfCQux8IbATOcvcXgzwXBT2iO/LagYRPBZ6IiIhIyVQxKEjmAD8DE4P2L939x+D+CUCPYL1ZQG0iRUB2XYFng/tPRrWfENy+AuYRKdRaEykmjzezu8zsSHfflG1/nYEP3X29u+8mchpitJfdPTM4nXOfXF5f1ima+xMpKJ8wMwNymwQ6uv2l4OdcoFlw/1NgtJldDdTI6okDfgiep31Q/I3LZf/1gTW5LMtuNVGnRBbQEQT/Fu7+PlDbzKrls82P7j4/uB/92iWJFPm51SIiIiKSEHYEBckfIvUP26KbgKvc/a1s690OnAIQtY+cCicD7nT3R/6ywKwjcDJwm5m95+637kH2XdmeI0/u/rmZ1QHqAuuAmtlWqQWszWH/GQR/L7v7v83sjSDzp2b2d2DnHmTeAVSIcd0K/K+HMC+LgU7AK3uQI50/d/JEZ4r+vWYAOh0zCakHT0RERERy8xZwhZmVBTCzfc2ssrv/K6rHCiK9W1nXjF2UbfteZlYl2L6hmdULTsHc7u5PAfcQOS002mzgaDOrGZxCetbevIjgOrrSRIq774AGZnZAsKwp0A6Yn88+Wrr7Qne/K8iX/bTR/KQCrWJcd18ig7DkZyxwiZkdGpXzzGDwlY8J/i3MrBuR0043Az8R/L6DIjunU26z20LhD9wicaIePBERERHJzQQip+nNC05vXAP8I4f1BgLPmNkNRPUmufvbQSH1edA7uBXoTqTQucfMMoHdwBXRO3P3lWZ2B/AlsB74Bsh+Gmd+sk5BhUgv3yXungFkmFl34DEzqxA8f58cThPNbpCZHQNkEuk5m07ktMtYTSfq9FUz+yfwIJFexTfMbL67/z1YfAzwRn47DAZTOR+418zqBdk+InJN40hgkpktALYDlwSbTSVy2u1iIqfdfhtD9snAODPbAXTRdXiJzdxzOw1ZRERERCQcZlbF3bcGPXjTgEnuPi3sXHvDzKYB17v7d3msUx74EDgi6jq/rGU9gRR3HxDXoDGwyFx9rweDsEgC0SmaIiIiIpKIRgY9cIuAH4GXQ01TOIaSf69fE2Bo9uIusAM4yaImOg+DmT0NHM2eXYMoRUQ9eCIiIiIiIsWEevBERERERESKCRV4IiIiIiIixYQKPBERERERkWJCBZ6IiIiIiEgxoQJPRERERESkmPh/2FH7EMsMsjkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1080x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "metric = \"bunsh\"\n",
    "boxlabel_x = ''\n",
    "boxlabel_y = 'Buried Unsat. polar atoms (1) [Count]'\n",
    "scattlabel_x = 'Pre-design BUnsH (1) [Count]'\n",
    "scattlabel_y = 'Post-design BUnsH (1)  [Count]'\n",
    "\n",
    "make_plot(all_data, metric, boxlabel_x, boxlabel_y, scattlabel_x, scattlabel_y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Buried unsatisfied polar atoms (Filter #2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Median pre-design: 5.00 / Median post-design: 5.00\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "metric = \"bunsh2\"\n",
    "boxlabel_x = ''\n",
    "boxlabel_y = 'Buried Unsat. polar atoms (2) [Count]'\n",
    "scattlabel_x = 'Pre-design BUnsH (2) [Count]'\n",
    "scattlabel_y = 'Post-design BUnsH (2)  [Count]'\n",
    "\n",
    "make_plot(all_data, metric, boxlabel_x, boxlabel_y, scattlabel_x, scattlabel_y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Shape complementarity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Median pre-design: 0.63 / Median post-design: 0.60\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "metric = \"sc\"\n",
    "boxlabel_x = ''\n",
    "boxlabel_y = 'Shape complementarity'\n",
    "scattlabel_x = 'Pre-design shape compl. [Count]'\n",
    "scattlabel_y = 'Post-design shape compl. [Count]'\n",
    "\n",
    "make_plot(all_data, metric, boxlabel_x, boxlabel_y, scattlabel_x, scattlabel_y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Buried surface area (dSASA)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Median pre-design: 1003.67 / Median post-design: 959.54\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "metric = \"sasa\"\n",
    "boxlabel_x = ''\n",
    "boxlabel_y = 'dSASA [A^2]'\n",
    "scattlabel_x = 'Pre-design dSASA [A^2]'\n",
    "scattlabel_y = 'Post-design dSASA [A^2]'\n",
    "\n",
    "make_plot(all_data, metric, boxlabel_x, boxlabel_y, scattlabel_x, scattlabel_y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Contact molecular surface (CMS)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Median pre-design: 174.29 / Median post-design: 176.12\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "metric = \"cms\"\n",
    "boxlabel_x = ''\n",
    "boxlabel_y = 'Contact molecular surface (CMS)'\n",
    "scattlabel_x = 'Pre-design CMS'\n",
    "scattlabel_y = 'Post-design CMS'\n",
    "\n",
    "make_plot(all_data, metric, boxlabel_x, boxlabel_y, scattlabel_x, scattlabel_y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Similarity score, small molecule contacts and beta sheet ratio\n",
    "The **similarity** score gives an alignement score with all other seeds. A score of 0 is a unique seed, while a score of 1 means the seed is identical with another one.\n",
    "\n",
    "The **small molecule atom contacts** give the number of atoms that the seed has in contact with the target drug. This ensures that at a minimum contact is performed by the seed with the small molecule.\n",
    "\n",
    "The **beta sheet ratio** is only computed and meaningful for beta sheet-based seeds as the subsequent grafting steps will crop loop regions to increase grafting efficiency. Therefore, only seeds with a high number of beta sheet-based contacts should be selected.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Similarity median: 0.45\n",
      "Small molecule contacts median: 11.00\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA24AAAEGCAYAAAAdacZ5AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuNSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/xnp5ZAAAACXBIWXMAAAsTAAALEwEAmpwYAABIXElEQVR4nO3deXycZb3//9dnsu97lzRbW7pQCi1tadkOlkUEZHFBARFZrXpERUQ9qAeX39Gv20E94kErIIsIAoKCB5V970JbulJaWtom3ZOmSZqk2T+/P+ZuCSFt0zSTmSTv5+Mxj7nnnnvu+3NlJnPN576u+7rM3REREREREZHYFYp2ACIiIiIiInJwStxERERERERinBI3ERERERGRGKfETUREREREJMYpcRMREREREYlx8dEOoLP8/HwvKyuLdhgiPbdmTfh+woToxiEywCxevLjK3QuiHcdAofpRhhzVrzKEHaiOjKnEraysjEWLFkU7DJGemz07fP/CC9GMQmTAMbNN0Y5hIFH9KEOO6lcZwg5UR6qrpIiIiIiISIxT4iYiIiIiIhLjlLiJiIiIiIjEOCVuIiIiIiIiMU6Jm4iIiIiISIxT4iYiIiIiIhLjIpa4mdkEM1va6VZnZjdE6ngiIiLRZmbJZrbQzJaZ2Soz+3432ySZ2Z/NbJ2ZLTCzsiiEKiIiA0zE5nFz9zXAVAAziwO2AI9F6ngiIiIxoBk4w93rzSwBeMXM/uHu8zttcy2w292PMrNLgZ8Al0QjWBERGTj6q6vkmcB6d9eEqyIiMmh5WH3wMCG4eZfNLgLuCZYfAc40M+unEEVEZIDqr8TtUuCB7p4wszlmtsjMFlVWVvZTOCI9U1xSipkd8PbCiy/ywosvHnSbWLgVl5RG+08pMmSYWZyZLQV2Ak+7+4Ium4wCKgDcvQ2oBfK62Y/qRxnS5s2fr/pR+tShftfF+ucpYl0l9zGzROBC4Obunnf3ucBcgBkzZnQ9KykSVZsryrn1qTUHfH7sTVcAcOvP7+uvkHrlxrMnRDsEkSHD3duBqWaWDTxmZpPdfWUv9qP6UYa05ubmg9bBfUH149ByqN91RyrSn6f+aHE7F1ji7jv64VgiIiIxwd1rgOeBc7o8tQUoBjCzeCAL2NWvwYmIyIDTH4nbZRygm6SIiMhgYmYFQUsbZpYCfBB4q8tmjwNXBssXA8+5u1rURETkoCLaVdLM0ghXWp+L5HFERERixEjgnmA05RDwkLv/3cx+ACxy98eBO4H7zGwdUE34OnAREZGDimji5u4NdHPBtYiIyGDk7suB47tZf0un5SbgE/0Zl4iIDHz9NaqkiIiIiIiI9JISNxERERERkRinxE1ERERERCTGKXETERERERGJcUrcREREREREYpwSNxERERERkRinxE1ERERERCTGKXETERERERGJcUrcREREREREYpwSNxERERERkRinxE1ERERERCTGKXETERERERGJcUrcREREREREYpwSNxERERERkRinxE1ERERERCTGKXETERERERGJcUrcREREREREYpwSNxERERERkRinxE1ERERERCTGKXETERERERGJcRFN3Mws28weMbO3zGy1mZ0UyeOJiIiIiIgMRvER3v+vgH+6+8VmlgikRvh4IiIiIiIig07EEjczywJOA64CcPcWoCVSxxMRERERERmsItlVcjRQCfzBzN4wszvMLK3rRmY2x8wWmdmiysrKCIYjIiIiIiIyMEUycYsHpgG3u/vxQAPwH103cve57j7D3WcUFBREMBwREREREZGBKZKJ22Zgs7svCB4/QjiRExERGZTMrNjMnjezN81slZl9pZttZptZrZktDW63RCNWEREZWCJ2jZu7bzezCjOb4O5rgDOBNyN1PBERkRjQBnzN3ZeYWQaw2Myedveu9d/L7n5+FOITEZEBKtKjSn4JuD8YUfId4OoIH09ERCRq3H0bsC1Y3mNmq4FR6MSliIgcoYgmbu6+FJgRyWOIiIjEIjMrA44HFnTz9ElmtgzYCtzk7qu6ef0cYA5ASUlJBCMVEZGBIKITcIuIiAxFZpYO/AW4wd3rujy9BCh19ynAr4G/drcPDd4lIiKdKXETERHpQ2aWQDhpu9/dH+36vLvXuXt9sPwkkGBm+f0cpoiIDDBK3ERERPqImRlwJ7Da3W89wDYjgu0ws5mE6+Jd/ReliIgMRJEenERERGQoOQW4AlhhZkuDdd8CSgDc/bfAxcAXzKwN2Atc6u4ehVhFRGQAUeImIiLSR9z9FcAOsc1twG39E5GIiAwW6iopIiIiIiIS45S4iYiIiIiIxDglbiIiIiIiIjFOiZuIiIiIiEiMU+ImIiIiIiIS45S4iYiIiIiIxDglbiIiIiIiIjFOiZuIiIiIiEiMU+ImIiIiIiIS45S4iYiIiIiIxDglbiIiIiIiIjFOiZuIiIiIiEiMU+ImIiIiIiIS45S4iYiIiIiIxDglbiIiIiIiIjFOiZuIiIiIiEiMi4/kzs1sI7AHaAfa3H1GJI8nIiIiIiIyGEU0cQuc7u5V/XAcERERERGRQUldJUVERERERGJcpBM3B54ys8VmNqe7DcxsjpktMrNFlZWVEQ5HRERERERk4Il04naqu08DzgW+aGandd3A3ee6+wx3n1FQUBDhcERERERERAaeiCZu7r4luN8JPAbMjOTxREREREREBqOIJW5mlmZmGfuWgbOBlZE6noiIiIiIyGAVyVElhwOPmdm+4/zJ3f8ZweOJiIiIiIgMShFL3Nz9HWBKpPYvIiIiIiIyVGg6ABERERERkRinxE1ERKSPmFmxmT1vZm+a2Soz+0o325iZ/Y+ZrTOz5WY2LRqxiojIwBLJa9xERESGmjbga+6+JBiga7GZPe3ub3ba5lxgXHCbBdwe3IuIiByQWtxERET6iLtvc/clwfIeYDUwqstmFwH3eth8INvMRvZzqCIiMsAocRMREYkAMysDjgcWdHlqFFDR6fFm3p/cYWZzzGyRmS2qrKyMWJx9qbikFDOL6K24pDTaxZRAJN/vF158MdrFE4k56iopIiLSx8wsHfgLcIO71/VmH+4+F5gLMGPGDO/D8CJmc0U5tz61JqLHuPHsCRHdv/RcJN/vsTddwfrlCyOyb5GBSi1uIiIifcjMEggnbfe7+6PdbLIFKO70uChYJyIickBK3ERERPqImRlwJ7Da3W89wGaPA58JRpc8Eah19239FqSIiAxI6iopIiLSd04BrgBWmNnSYN23gBIAd/8t8CRwHrAOaASu7v8wRURkoFHiJiIi0kfc/RXADrGNA1/sn4hERGSwUFdJERERERGRGKfETUREREREJMYpcRMREREREYlxStxERERERERinBI3ERERERGRGKfETUREREREJMYpcRMREREREYlxStxERERERERinBI3ERERERGRGKfETUREREREJMZFPHEzszgze8PM/h7pY4mIiIiIiAxGPUrczOyUnqw7gK8Aqw8nKBERkWg7wrpPRESkT/W0xe3XPVz3HmZWBHwYuONwghIREYkBvar7REREIiH+YE+a2UnAyUCBmd3Y6alMIK4H+/8l8A0g4yDHmAPMASgpKenBLkVERCKnD+o+ERGRPneoFrdEIJ1wgpfR6VYHXHywF5rZ+cBOd198sO3cfa67z3D3GQUFBT0OXEREJEJ6XfeJiIhEykFb3Nz9ReBFM7vb3Tcd5r5PAS40s/OAZCDTzP7o7p/uZawiIiIRd4R1n4iISEQcNHHrJMnM5gJlnV/j7mcc6AXufjNwM4CZzQZuUtImIiIDyGHXfSIiIpHS08TtYeC3hAcZaY9cOCIiIjFDdZ+IiMSMniZube5+e28P4u4vAC/09vUiIiJRcER1n4iISF/q6XQAT5jZv5vZSDPL3XeLaGQiIiLRpbpPRERiRk9b3K4M7r/eaZ0DY/o2HBERkZihuk9ERGJGjxI3dx8d6UBERERiieo+ERGJJT1K3MzsM92td/d7+zYcERGR2KC6T0REYklPu0qe0Gk5GTgTWAKo8hIRkcFKdZ+IiMSMnnaV/FLnx2aWDTwYiYBERERigeo+ERGJJT0dVbKrBkB9/0VEZCg5ZN1nZneZ2U4zW3mA52ebWa2ZLQ1ut0QkUhERGXR6eo3bE4RH0gKIA44GHopUUCIiItHWy7rvbuA2Dt6d8mV3P/+IAxQRkSGlp9e4/bzTchuwyd03RyAeERGRWHHYdZ+7v2RmZRGNSkREhqSeXuP2opkN590Ltd+OXEgisaetvYM9TW00tLTR0NxOY0sbbR3Oh5pacYeFG6pJig+FbwlxZKUkkJkST3yot72RRSTaIlj3nWRmy4CtwE3uvqq7jcxsDjAHoKSkpI8OLSIiA1VPu0p+EvgZ8AJgwK/N7Ovu/kgEYxOJir0t7bxRvptFm3aT/5GbuXfeRmoaW/f3l+qsbm8rAPPe2fW+5wzISI4nPz2JkdnJFGalMCwzScmcyAARobpvCVDq7vVmdh7wV2Bcdxu6+1xgLsCMGTO6+woSEZEhpKddJb8NnODuOwHMrAB4BlDiJgOeu7Nmxx7+tXIHL79dybLNNbS2O2aQWDCa3LRExg3PICclgbSkeNKS4klNjCMuZIx6MgUMrj/9KJrb2mlu62BvSzu1e1upaWylprGFHXuaeaeqAYC4kFGSm8rYgjRG56eRmtjTf0ERiYI+r/vcva7T8pNm9r9mlu/uVUccrYiIDGo9/dUY2ldxBXbR+xEpRWLC6m11PPbGFv65cjvl1Y2YwXFF2Vxz6mhOHJ3H9LIcslISuempNQfeiRkQTshSE+NJTYScVCjMTnnPZo0tbWyrbWJz9V7WV9WzoaoBA4pyU5hcmMWYgjS1xInEnj6v+8xsBLDD3d3MZgb7e3+TvYiISBc9Tdz+aWb/Ah4IHl8CPBmZkEQip7axlcfe2MwjSzazcksdCXHGKUfl8/kPjOWsScMYlpEckeOmJsYztiCdsQXpnDY+n6r6FtbtrGf19jr+sXI7KQlxHD0yg6nF2WQkJ0QkBhE5bIdd95nZA8BsIN/MNgPfBRIA3P23wMXAF8ysDdgLXOru6gYpIiKHdNDEzcyOAoa7+9fN7GPAqcFT84D7Ix2cSF95e8ce/vDaRh5bsoW9re0cU5jJ9y6YxIVTR5GbltivsZgZBRlJFGQkceKYXMqrG1m5tY6lFTUsrahh4ohMZpTmkNPPcYlI2JHUfe5+2SGev43wdAEiIiKH5VAtbr8EbgZw90eBRwHM7NjguQsiGJvIEXt9YzW/fm4dL62tJDE+xEemFnLlyWUcU5gV7dCAcBJXmpdGaV4adU2tLNm0m1Vb63hzWx3jh6dzyth8MlPUAifSz36J6j4REYkxh0rchrv7iq4r3X2F5qmRWLbgnV386tm3eW39LvLTE7np7PFcNrOEvPSkaId2QJnJCcyeMIyZo3N5ozzc+rZ+ZwNTirM4oSyX5IS4aIcoMlSo7hMRkZhzqMQt+yDPpRzkOZGoWPDOLn75zNvMe2cX+elJfOfDR3P5rFJSEgdO0pOaGM8pR+VzXFEW89+pZkl5DW9ureOUcfkcMzITCwZEEZGIyT7Ic6r7REQkKg6VuC0ys8+6++87rzSz64DFkQtL5PC8vWMPP3pyNc+vqaQgI4n/PH8Sn5pZMqAStq4ykhP44KThTC3O5oW1O3l29U5Wb63jjInDYrrlUGQQUN0nIiIx51CJ2w3AY2Z2Oe9WVjOAROCjEYxLpEd21Tfzy2fe5k8Ly0lNiOPmcydy5cllg6pbYUFGEhdPK+LNbXW88nYVf1pYzglluZxQlktcSK1vIhFwA6r7REQkxhw0cXP3HcDJZnY6MDlY/X/u/lzEIxM5iOa2du5+dSO3PbeOxtZ2Lp9VwlfOHDdoW6LMjGMKsxidn8ZLb1exYEM1G6oa+NAxI/p9VEyRwU51n4iIxKIezePm7s8Dzx/Ojs0sGXgJSAqO84i7f/ewIxTp4pW3q/jPv61kQ1UDZ0wcxrfOm8hRwzKiHVa/SE2M55xjRjA2P43n1uzkTwvLOfWofKYUZenaN5E+1pu6T0REJFJ6OgF3bzQDZ7h7vZklAK+Y2T/cfX4EjymD2I66Jv7r/1bzxLKtlOWlcs81M/nA+IJohxUV44ZnUJidwjOrd/Di2koqqhv54KThg6qLqIiIiIi8K2KJm7s7UB88TAhuHqnjyeDV1t7BffM38d9PraWlvYMbzhrH5z8wdsgnKWlJ8Vw4pZClFTW8sq6KBxaWc+6xIxmRmRzt0ERERESkj4UiuXMzizOzpcBO4Gl3X9DNNnPMbJGZLaqsrIxkONLPiktKMbMjuiXkF1N89a/4/hNvUvnWQjb873V89YMTSEmMP+J99+QW68yM40ty+MT0Yhx4eFEFyzfXRDssEREREeljkewqibu3A1PNLJvwCF2T3X1ll23mAnMBZsyYoRa5QWRzRTm3PrWmV6/tcGdpeQ2vvbOLhDhj9vhhjD/jk9h1l/RxlAd349kT+vV4vTUiK5lPzSzhX6u28/yaSqrqW/jA+AKNOikiIiIySEQ0cdvH3WvM7HngHGDlobaXoa2msYWn3tzBttomxhakcfqEYaQl9ctHdUBLTojjgimFvLZ+F4s37aa6oYUPHztyQM9lJyIiIiJhEfs1bGYFQGuQtKUAHwR+EqnjycDn7izfXMsr66oIhYyzJw1n4oiMAdFlMVaEzDj1qHzy0xN5ZvVOHny9nPOPK4x2WCIiIiJyhCLZjDESuMfM4ghfS/eQu/89gseTAaxubytPr97B5t17Kc1N5cyjh5GRnBDtsAasiSMyyU5J5O/Lt/Lw4gpSjpoV7ZBERERE5AhEclTJ5cDxkdq/DA7uzqptdby8tgrHOXPiMI4pzFQrWx8YkZXMpTNL+PvyrbR87NvcO28jnzmpLNphiYiIiEgvRHRUSZGDqW9u4/FlW3l29U6GZSTx6VmlTB6liaT7UnpSPB+fVsTedQu55W+r+Mk/3yI8U4eIiIiIDCQa8UH6nbuzZsceXlhTSXuH84HxBUwpUsIWKQlxISof+xE3/2Upt7+wnh21Tfz448eRGK/zNiIiIiIDhRI36VeNLW0899ZO1lc2MDIrmQ9OGk5OamK0wxr8vIMffmQyhVnJ/Pyptezc08ztn56m6whFREREBgglbtJv3t65h+ffqqSlrYNTjspjWkkOIbWy9Rsz4/ozxjE8M5n/eHQFl86dzz3XzCQ/PSnaoYmIiIjIIaivlERcU2s7/1y5nSdXbCcjOZ7LZhYzozRXSVuUfGJGMXdeOYP1lfV88nfz2Fa7N9ohiYiIiMghKHGTiNpQ1cAf52/i7Z17OHF0Lp+cUUyeWniibvaEYdx37Swq65q5+PZ5bKxqiHZIIiIiInIQ6iopEbGnqZW8c7/M48u2kpeWyIVTCxmWkRztsKSTE8pyeWDOiVxx5wI+8bt5/PHaWUwYkRHtsEREZKCwEI0tbTS3ddDU2k5LWwdtHU5bu9Pe4bR1dNDe4XQey3hfX5u4kBEfChEfZ+FbKERifIjk+BApCXGARkAW6UqJm/S5V9dV8Y1HlpM2+UxmlOYwa0wu8SE17saiyaOyeOhzJ/HpOxdwydx53HP1TKYUZ0c7LBERiaKODmfnnmY2725ke10T22ub2Lmnme21TWyva2JnXRNV9S2UfuNxfv/yhojEMHv3XpJGHc198zaRnhxPWlIcGUkJ4fvkBLJSwre4kC67kKFDiZv0mcaWNn78j7e4d94mxuSnsf2PX+eUe56IdlhyCOOGZ/Dw507m8jvnc/kdC7jzyhnMGpMX7bBERCSC3J3K+mbW7axnY1Ujm3Y1sHFXA5t2NbJxVwNNrR3v2T4pPsTwzGRGZCYzeVQW+elJ/PIn/8VF136V5PgQSQlxJMWH9reexYeMuOC2/5J2f/cu3CLntLV30Brct7R10NTaQVNbOxnJCeyuqiYnLYH65jaqG1poaN7zvta7jOR4slMTyU5NIDslgZzURPLTk0hLitM0QzLoKHGTPvH6xmpuengZ5dWNXHPKaL7+oQmkfn1ttMOSHirJSw0nb3fM5zN3LeS3V0zn9AnDoh2WiIj0gbqmVt7esYe3tu9h7fY9rNmxhzXb97C7sXX/NolxIUryUinLS+WUo/Ipy0+jOCeFkVkpDM9MIisl4X2J0PcvepCp3/t+RGLOTEmgcvdWzj+ucP+6jg6nsaWdPc2t1DQGt70t1DS28ta2Jlra3002kxNC5KcnkZ+eREF6EvnpieSmJRIfpx5AMnApcZMj0tTazn8/tYY7XtlAUU4KD372RLXWDFAjspJ56HMn8Zm7FjLn3kX8+rJpnDN5RLTDEhGRw1DT2MLKLXWs2FLLii01rNhSS0X1u6MHpyXGMX5EBh86ZgTjh2cwbng6o/PTGJmVEvPdDkMhIz05nvTkeEZmpbznOXdnb2s7uxtaqapvprK+mar6ZlZuqaWtI9xOFzLIT09iRGYyI7KSGZ6ZzLtX3YnEPiVu0mtLK2r42kNLWV/ZwOWzSvjWeUeTlqSP1ECWl57Enz57Ilf9YSFf/NMSfnHJVC6cUnjoF4oIAGZ2F3A+sNPdJ3fzvAG/As4DGoGr3H1J/0Ypg8WeplaWVdSyfEsNK7fUvi9JK85N4dhRWVx6QgkTR2QwfngGo7JTCMV4gtYbZkZqYjypifGMynk3qetwp7axlcr6ZnbuaWZHXROrt9exfEstAEVfeYAr7lzA8cXZnDA6l2klOfotIzFLn0w5bE2t7fzq2bf53YvrGZ6ZzL3XzOS08QXRDkv6SFZKAvddO4tr7n6dGx58g5a2Di6eXhTtsEQGiruB24B7D/D8ucC44DYLuD24Fzkod2d9ZQNLynfzRvlulmyqYe3OPXhw0de+JO1TM0s5dlQWk0dlkp2aGN2gY0DIjJy0RHLSEhk/PDxycoc7uxta2F7XxGN/+ge7RhfymxfW0/7cOuJCxuTCTGaOzuWEsvAtJ01/R4kNStzksCytqOHrDy/j7Z31fHJGEd85fxKZyQnRDkv6WHpSPPdcPZPP3ruImx5eRktbB5+aVRLtsERinru/ZGZlB9nkIuBed3dgvpllm9lId9/WPxHKQFHf3MayihqWbNodTtYqaqgJrknLSI7n+JIczj12BNNKcjiuKEtJ2mEImZGXnkReehJ3PvUbnvzXbdQ3t7Fk025e31jNgg3V3DNv0/4RM8cPT2fm6Fxmjc7jpLF55Gs+WokSJW7SI11b2e6++gRma/CKQS0lMY47rpzBv9+/hG89toLmtnauPmV0tMMSGehGARWdHm8O1r0vcTOzOcAcgJKSIz9xUlxSyuaK8iPeT9RZKOKjBRYVl1BRvimix+jM3dlQ1cCS8hqWlO9myabdrN2xh+DSLMYNS+dDk0YwrTSbaSU5jC1IP2R3x0HzfveT9KR4ThtfsL8HUXNbO8s317JwQzULN1Tz1ze28sf54b/nxBEZnDw2n1OOymPm6FwyDnECO9LvRX98Xvvj89Tf/3cDkRI3OaTOrWyXzCjm2+cfrVa2ISI5IY7ffno6X3pgCd9/4k2aWjv4wuyx0Q5LZEhw97nAXIAZM2Yc8WzEmyvKufWpNUcc18HcePaEiO4fAO8Y8OXY29LO8s01LC7fzeKN4da06oYWADKS4plaks2HjhnBtNIcphZnk5Vy+HXuoHm/oyQpPm5/V8kvng5t7R2s3FrHq+uqeG19Ffcv2MRdr24gLmQcV5TFKWPzOfmoPKaV5JCcEPeefUX6veiP90Gfp9igxE0OqKm1nV8+8zZzX1Ir21CWGB/itk9N48aHlvGTf75Fc1s7XzlznObHEemdLUBxp8dFwToZxLbV7mXxpt0s3hRuTVu1tW7/SIdjCtI4Y+IwppfmMK0kh6OGpcf86I5DUXxciKnF2UwtzuaLpx9FU2s7S8p389q6Xby6vorbX1zPbc+vIyk+xIyynKBFLp/JhZnRDl0GESVu0q0l5bv5xiPLWadWNgES4kL88pKpJMWH+OUzb9PU2sE3z5mg5E3k8D0OXG9mDxIelKRW17cNLq3tHby1bQ+LN1WzKEjUttY2AeG5xaYUZTPntDFML83h+JIccjXwxYCUnBDHyWPzOXlsPjcxgT1NrSzcUM2r63bx2voqfvavNfzsX2vISIqn4GPf4Y3y3RTnppKXlqi6U3pNiZu8R31zGz/751vcO38TI9TKJp3EhYyffvw4kuJD/PbF9TS3tXPL+ZNUAYl0YmYPALOBfDPbDHwXSABw998CTxKeCmAd4ekAro5OpNJXahpbWFK+e3+L2rKKWva2tgMwMiuZ6aU5fLY0h+mlORw9MpMETQA9KGUkJ3Dm0cM58+jhAFTVNzNvfTiJu3d7CS+9XQVASkIcxTkpFOemUpST0u3E5iIHosRN9nvmzR38599Wsr2uiStPKuOmD00gXXOZSCehkPFfH5lMUnwcd726gea2Dv7rosmDck4gkd5w98sO8bwDX+yncKSPtXc4b+/cE4z2WMOiTdWsr2wAwie3jinM5JITipkeJGqF2SmH2KMMVvnpSVwwpZALphTy449P4Xt/W0nF7kY2795LRXUja3fWA+ERQotzUinOSaEoN1W/u+SgIvbpMLNiwvPYDAccmOvuv4rU8aT3du5p4vuPv8n/rdjGhOEZ/ObyaUwryYl2WBKjzIz/PP9okhJC3P7CelraOvjJx4/TNRkiMqi4O9tqm1hWUcPSzTUsLa9hxZZaGlvCrWnZqQlML8nhY9OKmF4aHpI/NVE/uqV7mSkJHJOSxTGFWbg7uxtbqdjdSEV1I+sr63lzWx0AOakJFOekUpSbQlFOKildBjqRoS2S3zBtwNfcfYmZZQCLzexpd38zgseUw9DR4Ty0qIIfPbmaprYObjp7PHNOG0tivLpxyMGZGd/40ASS4+P4xTNraW7r4NZPTlEXIBEZsJrb2tlR18yOuiYKPvptZv3oWXbuaQYgMS7E0YWZfGJ6EVNLsplSlE1ZXpp6G0ivmBm5aYnkpiUypSgbd6eyvpnN1Xsp393I6u11LN9SC0BBRhKjslMozE6mMCuFNLXIDWkRe/eDi623Bct7zGw14blqlLjFgDe31nHL31ayaNNuZo3O5f997FjGFKRHOywZQMyMr5w1jqSEED/+x1u0tLXzP5cdT1K8zg6KSGxr73Cq6sNJ2va6JnbUNlPd2LL/+YS8Yk45Kp+pxdlMKc7m6JEZ+m6TiDEzhmUkMywjmWmlObR3ODvqmsJdK6v3smJLLUsraoBwS284kUthVHYKmclK5IaSfnm3zawMOB5Y0B/HkwOra2rlF0+v5Z7XNpKdmshPLz6OT0wv0oWx0muf/8BYkuJDfP+JN/n8fYu5/dPT3zeHjYhItLg7tXtb2VHXHE7S6prYuaeZ9mA4/pSEOEZkJTN+RDojMpMZnpnMtz58Pr/4/RFPnSfSK3EhozBIzmaNDp9o2LmniS01e9la08S6nfWs2hruWpmWFEf+hd/gntc2Mr00h4kjMohX75dBK+KJm5mlA38BbnD3um6enwPMASgpKYl0OANCpGanT5s0m+zTryEuLZv6N/7Bppfv45Jb6rmkz48kQ83Vp4wmKT6Ob/91Bdfds4i5n5muaz26Ean/7f5WVFxCRfmmaIch0q29Le37W9L2JWpNrR0AxIeMYRlJHFeUxYjMZEZkJpORHK+TlxLT4kLGyKwURmalQGn4ZMSuhpYgkdtLbdEkvvv4KiA85cSxo7KCOedymFqSTWFWsj7jg0REf1mZWQLhpO1+d3+0u23cfS4wF2DGjBk6vUXfz05fVd/MC2sq2VKzl+GZSZw+YRjDz7oBvn5Dnx2jOzeePSGi+5fY8qlZJSTGh/jGI8u46q7XuevqEzQ6Vhd9/b8dLfrflljR1t7Bzj3vtqTtqGumdm/r/ufz0hIZk5/OiKxwkpablqiBlGTAMzPy05PIT09iSlE2T984m/JdDSwp383SihqWVtRwz2ub+H37BiB8ndy+ycOPL87muOJs1c8DVCRHlTTgTmC1u98aqePIgTW1trNgQzXLN9eQGBfizInDOKYwU2ddJGIunl5EUnyIG/68lCvuXMDdV88kK0UTt4vIketwZ3dDC2nHnsWzb+1gR10zu+qbCXo8kp4Uz4jMZCaPymREZvh6IQ22JUNFcW4qxbmpXDR1FAAtbR2s3la3P5FbWlHD02/uAMAMRuelMakwk2MKszimMJNjCjPJS0+KZhGkByKZbp8CXAGsMLOlwbpvufuTETymEO4LvWJLLfPf2UVLWwfHjMrk5DH5pCTquiOJvAumFJIQF+JLDyzh8jvmc981s8hJS4x2WCIywDQ0t7Gt9t3ujjvrmmlp7yD/vBtYu72e4VlJTC/NYXjQ5VGj7Ym8KzE+xJRgcJ0rg3U1jS0srahh+eZaVm0ND3jy9+Xb9r9mRGby/iRuUpDQFeWk6IR/DInkqJKvAHqn+5G7s3FXIy+/XcnuxlaKc1M4bVwB+TqDIv3snMkjmHvFDD73x8Vc9vv53HftLAoy9DkUke51uLOrvoVttXvZVtvEttqm/V0eQxbu6jVxZAYjMpP5w1c/yk8eeEY/JkUOU3ZqIrMnDGP2hGH719U0tvDm1jpWba1j1dZaVm2t4/k1O/e3ZGckxTN+RAa5H/oiyypqyEtPJC8tSY0BUaLTU4PErvpmXn67ik3VjWSnJnDBlJGMzktTxSZRc/rEYfzhqhO49p7XuXTuPO6/7kRGZCVHOywRiQEtbR1sr2tiW81ettY2sb22iZb28AAiqYlxjMxK5rhRWYzMTqYgPek9o+S1VW9W3SbSR7JTEzn5qHxOPip//7q9Le28tT2czK3Zvoc1O/aQOuFUXlhbuX+b1MQ48tISyUtPIi89kfy0JHLTEtU9OcKUuA1w9U1tLNiwi1Xb6kiMC3HauHyOK8rWxdcSE045Kp97r5nF1X9YyCVz53H/dbMoykmNdlgi0s+a29rZWtPE5t2NbN69l8o9zewbjSw/PZEJIzIozEpmZDAvlRIzkehJSYzj+JIcji/J2b/O7GR+8MQqdtU3s6uhhV31LVTVN7NySy1tHe+OLZiZHB9O5tIS97fO5aQmaIqCPqLEbYBqam1n0abw6EHuzpRR2cwck0uK5s+SGDNzdC73XTeLK+9ayCW/m8/9182iLD8t2mGJSAQdKFGLM2NEVjInlOVSmJ3MiKxkTWwtMkCkJ8WTnhRPad67dfi+eRL3JXO76pupamhh066G/d0tjfDE4bn7WujSEslLSyQ7VaO8Hi4lbgNMa3sHyypqWLRpN81tHUwckcGJY/I0cp/EtGklOTzw2RO54s4FfPz217jrqhOYUpwd7bBEpI+0dzjba5vI/rcrePD1cnbWhRO1kBFO1EbnUpSdwsisZJ15FxlEzIzs1HASNrbg3fXtHU5NY8u7CV1DM7vqW3insmF/a3vIICf13Za5lHEnsrGqgeLcVCV0B6DEbYBo73BWb6tj/oZdNDS3U5aXyslj8zXggwwYk0dl8cgXTubKuxZy6dz5/O/l0zh94rBDv1BEYlJNYwubqhsp39VIxe5GWtudzBMvJmTGCWW5FOWkMCIrmQQlaiJDTlzIguvfkmD4u+vb2juobtyXzIVb6LbXNrF2Rz3DPvYdZv/8BZLiQ4wbns744RmMH57BhOEZjA+6Uw/1btRK3GJcR4ezensdr2/cTe3eVkZmJXPuMSMZlZMS7dBEDtvYgnQe/feTuebu17nu3kX86KOTueSEkmiHJSI90NreQUV1Ixt3NVJe3bh/1MfM5HgmjMigNDeN2689jRueWBLlSEUkVsXHhRiWEZ5nsbOWtg5uufYi7vvbM6zZsYe1O/bw6roqHl2yZf82WSkJHFOYyeRR++aey2J0ftqQap1T4hajOjqct3bsYeGGamr3tjIsI4kLjhvJ6HyNFCkD27CMZB6ccxL/fv8SvvmXFWytaeKGs8bpcy0Sgxqa29hQ1cA7VQ2UVzfS3uEkxBlFOakcX5xNSV4q2SkJ+/9/vbkhyhGLyECUGB+iZdtaPnlC8XvW1za2snbnHt7avoc3g+kK7n5tIy1t4VFoUxLigonEM5lcmMWkwkzGD88YtKNbKnGLMW3tHaQdcwb3zt9E7d5WCpSwySCUnhTPnVfO4FuPruBXz77Nlpq9/PCjkzVIgUiUuTvVDS28U9XAO5UNbK9rAiAjOZ7JhZmMKUinMDuZ+NDg/FEkIrElKzWBE8pyOaEsd/+61vYO1u2sZ9XWOlZuqeXNrXX8ZfFm7p23CQgngceOyuL44uxgdMxsCrMHR081JW4xoqWtg7++sYXbX1xP/vk3khgX4vzjRjJGCZsMUglxIX568XGMyknhl8+8zcaqBn57xXRNGC/Sz9ydHXXNrN25h3cqG/Z3gRyemcRJY/IYnZ9Gfnqi6iIRiQkJcSGOHpnJ0SMzuXh6ERDuqbapupGVW2pZvrmGN8pruHf+Ju54ZQMAIzKTOb4km8yZH2VLzV6GZyQNyIGSlLhFWUNzGw8sLOeOlzewva6JSSMz2fnoD/nybX9QJSmDnplxw1njOWpYOjc9vIyLbnuV339mBpMKM6Mdmsig1jlZW7eznj1NbYQMSnJTmV6aw+j8NNKT9BNBRAaGUMgYnZ/G6Pw0LphSCIQbRVZvq+ON8t28URFO5nJOv5ZHFm8mLmSMyExmVHYKo3LCI94OhIGU9K0cJbsbWrj7tY3cM28jNY2tnDgml59cfBynjcsndMM8JW0ypJx/XCGluWl89t5FfPz21/jFJVM5Z/KIaIclMuhsr216X7JWmpfGSWPyGJOfRpLmAhWRQSIxPsSU4mymFGdzVbAuLi2bf//9c2yp2cvm3Xt5fWM1CzeGpyYYnplMUU4Ko7JTGJmVEpPXySlx62dba/Zyx8sbeGBhOXtb2/ngpOF8YfZYpnWanV5kKDq2KIvHrz+FOfct5vN/XMxXzxrPl844itAQGi1KJFKef2snoz5/F39eVKFkTUSGrI7GWsYUpDOmIB2A5rZ2ttU0sblmL1t272XRpt28vnE3IYORWSmU5KVSmpvKsIykmGhUUeLWT1Zvq+POVzbwt6VbcIcLpxbyhQ+MZdzwjGiHJhIzhmUm8+CcE7n50RX84pm1LCnfzS8umUpuWmK0QxMZ0IZlJtFSuZHzTjpWyZqISCApPo6y/DTK8tOAcPfKbbV7qdi9l/LqRuat38W89btITghRkptKaW4aJXmpUetKrsQtgjo6nOfX7OTOVzbw2vpdpCTEcfmsUq77t9EU5aRGOzyRmJScEMetn5zCtNIc/r8n3uTD//Myt33qeKaX5h76xSLSrWMKs6j8yw84+nOXRzsUEZGYlRgfojQvjdK8cCLX2NJGeXUj5bsa2VTdyNod9QDkpSVSmpfK6Pw0CrNS+q13kBK3CGhobuMvSzbzh1c3sqGqgZFZyfzHuRO57IQSslIToh2eSMwzM644sZTji7P59/uXcMnv5vPNcyZy3b+NjomuCiIiIjL4pSbGM3FEJhNHZOLuVNW3UF7dyKZdDSytqGFJeQ1J8aH9SVwoOT2i8Shx60Nba/Zyz2sbeWBhOXVNbUwtzubXlx3POZNHDIiRakRizeRRWfz9y6fyjYeX88MnV7NgQzU/vfg4dZ0UERGRfmVmFGQkUZCRxPTSHFraOiivbmRDVQMbqhpYu6Oeoi/dT1V9c8SmNlLidoTcnXnv7OKP8zfxr1U7ADhn8giuOWU000s14IjIkcpMTuD2T0/jD69u5P/9YzUf+uVL/PTjx3H6xGHRDk2kW2Z2DvArIA64w91/3OX5q4CfAVuCVbe5+x39GqSIiByRxPgQRw1L56hh6funWLn9x/9J/k8vjNgxlbj1Uu3eVh5dspk/zt/E+soGslMTuO7U0Xzm5DJGDZLZ2UVihZlxzamjOXFMHjc+tJSr736dy2aW8J0PH02a5pqSGGJmccBvgA8Cm4HXzexxd3+zy6Z/dvfr+z1AERHpc2bGiKxk9ix+PKLH0S+ew7RySy1/nL+Jvy3dyt7WdqYWZ/Pfn5jCh48bSbJG6RKJqEmFmfzt+lO49am1zH35HV5aW8kPPzqZ2RPU+iYxYyawzt3fATCzB4GLgK6Jm4iIyGFR4tYDTa3t/N/ybdw3fxNLK2pITgjxkamj+PSJpUwelRXt8ESGlKT4OG4+72g+OGk43/zLcq76w+tcNLWQW86fRF6E+pSLHIZRQEWnx5uBWd1s93EzOw1YC3zV3Su6bmBmc4A5ACUlJREIVUREBhIlbgexbmc9Dy2q4OFFFexubGVMQRrfvWASH5tWRFaKRocUiaYZZbk8+ZV/4zfPr+f2F9bx4tpKvnb2BC47oZh4DQYkse0J4AF3bzazzwH3AGd03cjd5wJzAWbMmOH9G6KIiMSaiCVuZnYXcD6w090nR+o4fa2xpY2/L9/GQ69XsGjTbuJDxgcnDeeKk0o5aUyehiIXiSFJ8XHc+MHxnH/cSG7520r+868ruX/+Jr57wTGcNDYv2uHJ0LQFKO70uIh3ByEBwN13dXp4B/DTfohLREQGuEi2uN0N3AbcG8Fj9Al3Z2lFDQ8tquCJZduob25jTEEaN587kY9NK6IgQ92vRGLZ+OEZPPDZE/nHyu388P9Wc9nv5/PBScO56ewJTBiREe3wZGh5HRhnZqMJJ2yXAp/qvIGZjXT3bcHDC4HV/RuiiIgMRBFL3Nz9JTMri9T++0J1QwuPvbGFh16vYM2OPaQkxPHh40ZyyQnFzCjNUeuayABiZpx37EjOmDiMO15+h9+9+A7n/OolLppSyFc/OJ7SvLRohyhDgLu3mdn1wL8ITwdwl7uvMrMfAIvc/XHgy2Z2IdAGVANXRS1gEREZMKJ+jVtfX3xdXFLK5orygxwwRPLo40mffCap407C4hNo3rqG+uVP0bD6Jd5q2ct/H3EUIhItyQlxXH/GOC6fVcpvX1rPPa9t5Inl27jguJF87gNjOXpkZrRDlEHO3Z8Enuyy7pZOyzcDN/d3XCIiMrBFPXHr64uvN1eUc+tTa963vnJPM6u317Fm+x4aW9pJjg8xcWQmxxRmkp8+jvDleLHhxrMnRDsEkQEvJy2Rm889mmtOGc3vX3qHPy0s569LtzJ7QgHXnjqaU8bmEwqpVV1EREQGhqgnbpFU39zGmu17WL29jl31LYQMRuencfTITMry0ojTjzaRQW94ZjLfOX8S159xFPfN28Tdr23kijsXMjo/jU/NLOHi6UXkpCVGO0wRERGRgxp0iZvFJ/HW9jre2raH8upGHBiRmczsCQWMH55BiibJFhmSslMT+dKZ4/jsaWP458rt/HH+Jn745Gp+9q81zJ5QwEeOH8UZE4eRrO8IERERiUGRnA7gAWA2kG9mm4HvuvudkTpeW3sHNz+6gqLr7+Nfq3aQkRzPjLIcjh6RqbPpIrJfckIcHzl+FB85fhSrt9Xx8KLNPLF8K0+9uYOMpHhOnziMM48exuzxw8hK1XyNIiIiEhsiOarkZZHad3fi40Ls3NNM45pXuPKqqxmVnaJRIUXkoI4emcktF0zi2x8+mnnrd/H4si08u3onjy/bSlzImF6Sw4ljcjlxTB7TSnPUGiciIiJRM6i6St599QmErp1F0Ve/GO1QRGQAiQsZp47L59Rx+bR3OMs21/Ds6h28tLaK255fx/88t47EuBATR2Zw7Kgsjh2VxaTCTEbnp5GRPPBa5dyd9g6ntd1pbe8IbuHldnf2nfIys07LEDIjLmSEUrOjFLmIiMjQNagSN7WwiciRigsZ00pymFaSw9c/BHVNrSzaWM2CDdUsr6jl8WVbuX/Bu1OO5KcnUpqXRlleGqV5qRRkJJGXlkheehL56YnkpiWSlhjfqxEsO9xpa3faOjpo259kvT/ZamkPP9+yf30327V10NrRQWtbeP2RDOGbMfWcI3i1iIiI9MagStxERPpaZnICZ0wczhkThwPQ0eGUVzfy1vY9bNzVwMaqBjZUNfDKukr+sqT5gPtJjA9R9JUHueOVd4gPhTCDfdnTviRqX6LW3hFO1joOM7uKMyMhzoiPC5EYFyIh3kgIhUhPiiMh1UiICwW37pcT40KEQuD74tofn+Mejq+9w/nt718+vMBERETkiClxExE5DKGQUZafRll+2vuea2ptp7qhhV31LVQ1NLOrvoXqhmYaW9ppau3gp//9C4678NO0tTvepc3LMEIGcXFGfChEfMjCt7jwclychZOxbhKvxLgQ8XGhfpvipK16S78cR0RERN6lxE1EpI8kJ8RRmJ1CYXZKt8/ffN5czvrm1/o5KhERERkMQtEOQERERERERA5OiZuIiIiIiEiMU+ImIiIiIiIS45S4iYiIiIiIxDglbiIiIiIiIjFOiZuIiIiIiEiMU+ImIiIiIiIS45S4iYiIiIiIxDglbiIiIiIiIjFOiZuIiIiIiEiMU+ImIiIiIiIS45S4iYiIiIiIxDglbiIiIiIiIjFOiZuIiIiIiEiMU+ImIiIiIiIS45S4iYiIiIiIxLiIJm5mdo6ZrTGzdWb2H5E8loiISCw4VN1nZklm9ufg+QVmVhaFMEVEZICJWOJmZnHAb4BzgUnAZWY2KVLHExERibYe1n3XArvd/SjgF8BP+jdKEREZiCLZ4jYTWOfu77h7C/AgcFEEjyciIhJtPan7LgLuCZYfAc40M+vHGEVEZAAyd4/Mjs0uBs5x9+uCx1cAs9z9+i7bzQHmBA8nAGsiEtDhyweqoh1EhAzWsg3WcoHKNhAN1nJB35St1N0L+iKYWNKTus/MVgbbbA4erw+2qeqyr76uHwfLZ3IwlGMwlAEGRzlUhtgxGMrRV2Xoto6M74MdHxF3nwvMjXYcXZnZInefEe04ImGwlm2wlgtUtoFosJYLBnfZYklf14+D5X0bDOUYDGWAwVEOlSF2DIZyRLoMkewquQUo7vS4KFgnIiIyWPWk7tu/jZnFA1nArn6JTkREBqxIJm6vA+PMbLSZJQKXAo9H8HgiIiLR1pO673HgymD5YuA5j9R1CyIiMmhErKuku7eZ2fXAv4A44C53XxWp40VAzHXf7EODtWyDtVygsg1Eg7VcMLjLdkQOVPeZ2Q+ARe7+OHAncJ+ZrQOqCSd3/WGwvG+DoRyDoQwwOMqhMsSOwVCOiJYhYoOTiIiIiIiISN+I6ATcIiIiIiIicuSUuImIiIiIiMS4IZ+4mdk5ZrbGzNaZ2X908/yNZvammS03s2fNrDQacR6uHpTr82a2wsyWmtkrZjYpGnH2xqHK1mm7j5uZm9mAGVq2B+/bVWZWGbxvS83sumjEebh68p6Z2SeD/7VVZvan/o6xt3rwnv2i0/u11sxqohDmYetBuUrM7HkzeyP4fjwvGnFKz5lZXPB+/T3asfSGmWWb2SNm9paZrTazk6IdU2+Y2VeD77mVZvaAmSVHO6ZDMbO7zGxnMAfhvnW5Zva0mb0d3OdEM8aeOEA5fhZ8ppab2WNmlh3FEA+puzJ0eu5rwe+e/GjEdjgOVA4z+1Lwfqwys59GK76eOMDnaaqZzQ/q/EVmNrNPD+ruQ/ZG+MLx9cAYIBFYBkzqss3pQGqw/AXgz9GOu4/Kldlp+ULgn9GOu6/KFmyXAbwEzAdmRDvuPnzfrgJui3asESjXOOANICd4PCzacfdV2bps/yXCg1VEPfY+eM/mAl8IlicBG6Mdt26HfF9vBP4E/D3asfQy/nuA64LlRCA72jH1ogyjgA1ASvD4IeCqaMfVg7hPA6YBKzut+ynwH8HyfwA/iXacvSzH2UB8sPyTWC9Hd2UI1hcTHhRpE5Af7Th7+V6cDjwDJAWPY/q3wAHK8BRwbrB8HvBCXx5zqLe4zQTWufs77t4CPAhc1HkDd3/e3RuDh/MJz8kT63pSrrpOD9OAgTJKzSHLFvj/CH8BN/VncEeop2UbaHpSrs8Cv3H33QDuvrOfY+ytw33PLgMe6JfIjkxPyuVAZrCcBWztx/jkMJlZEfBh4I5ox9IbZpZF+EfSnQDu3uLuNVENqvfigZRgDr9UBsD/jru/RHgE1M4uIpxME9x/pD9j6o3uyuHuT7l7W/Aw5n/nHeC9APgF8A0GyO+5A5TjC8CP3b052CamfwscoAwRrRuHeuI2Cqjo9HhzsO5ArgX+EdGI+kaPymVmXzSz9YTPmn25n2I7Uocsm5lNA4rd/f/6M7A+0NPP48eDLh2PmFlxN8/Hmp6Uazww3sxeDboYnNNv0R2ZHn+HBN2sRwPP9UNcR6on5foe8Gkz2ww8Sbg1UWLXLwn/qOuIchy9NRqoBP4QdPe8w8zSoh3U4XL3LcDPgXJgG1Dr7k9FN6peG+7u24Ll7cDwaAbTR65hYPzOew8zuwjY4u7Loh3LERoP/JuZLTCzF83shGgH1As3AD8zswrC/+s39+XOh3ri1mNm9mlgBvCzaMfSV9z9N+4+Fvgm8J1ox9MXzCwE3Ap8LdqxRMgTQJm7Hwc8zbtnOwe6eMLdJWcTbpX6faxfZ9ALlwKPuHt7tAPpI5cBd7t7EeHuIPcF/38SY8zsfGCnuy+OdixHIJ5wl6Tb3f14oIFw97wBJbgO7CLCiWghkBb8vhjQPNwvbEC09ByImX0baAPuj3Ysh8PMUoFvAbdEO5Y+EA/kAicCXwceMjOLbkiH7QvAV929GPgqQS+BvjLUK9kthPsE71MUrHsPMzsL+DZw4b7m2xjXo3J18iADoItD4FBlywAmAy+Y2UbC//yPD5ABSg75vrn7rk6fwTuA6f0U25HoyedxM/C4u7e6+wZgLeFELtYdzv/apQyMbpLQs3JdS/j6HNx9HpAMxPwF8UPUKcCFwXfig8AZZvbH6IZ02DYDm919QfD4EcKJ3EBzFrDB3SvdvRV4FDg5yjH11g4zGwkQ3Md0t7aDMbOrgPOBy4MkdCAZS/hEwLLgf7wIWGJmI6IaVe9sBh71sIWEewgMtHrlSsL/1wAPE770oM8M9cTtdWCcmY02s0TCP6we77yBmR0P/I5w0jZQvpR6Uq7OP4o/DLzdj/EdiYOWzd1r3T3f3cvcvYxwf/UL3X1RdMI9LD1530Z2enghsLof4+utQ5YL+Cvh1jaC0bDGA+/0Y4y91ZOyYWYTgRxgXj/H11s9KVc5cCaAmR1NOHGr7NcopUfc/WZ3Lwq+Ey8FnnP3AdXK4+7bgQozmxCsOhN4M4oh9VY5cKKZpQYtCWcyML7Hu/M44R+pBPd/i2IsvRZ0zf8G4d8KjYfaPta4+wp3H9bpd89mYFrwPzPQ/JXwACWY2XjCgxBVRTOgXtgKfCBYPoM+/n0d35c7G2jcvc3Mric8Ck8c4dHeVpnZD4BF7v444a6R6cDDQWttubtfGLWge6CH5bo+aElsBXbz7pdvTOth2QakHpbty2Z2IeHuHNWER5mMaT0s17+As83sTaAd+Lq774pe1D1zGJ/HS4EHB8qZ3B6W62uEu7R+lXAXqasGSvlkwPoScH9wMuEd4Ooox3PY3H2BmT0CLCH8Pf4G4RFaY5qZPUD45Fp+cF3rd4EfE+7Kdi3hkQw/Gb0Ie+YA5bgZSAKeDn7nzXf3z0ctyEPorgzu3qfd8frDAd6Lu4C7guH1W4ArY7leOUAZPgv8Khh8qAmY06fHjOG/h4iIiIiIiKCukiIiIiIiIjFPiZuIiIiIiEiMU+ImIiIiIiIS45S4iYiIiIiIxDglbiIiIiIiIjFOiZsMGWb2bTNbZWbLzWypmc0K1t9hZpMOYz8zzOx/guWrzOy2w4yj8+tnm9lAnXxVRGRIOFD90Qf7rQ/uy4Ih0PuUmX3PzG7q433ebWYX98F+Yr7+M7NvHcFrD7t8ZjbSzP7e6fFMM3vJzNaY2RvB75XU3sZ0gGNeZWaFnR4/2GWuX4khQ3oeNxk6zOwk4HzCk1I2B5M8JwK4+3WHs69gMu9eTehtZvFdXj8bqAde683++oKZxbl7e7SOLyISyw5Wf8gRmU2U678e+Bbwo16+djaHX74bgd8DmNlw4GHgUnefF6y7GMgA+nKi8KuAlYQnjga4nfCE5J/tw2NIH1GLmwwVI4Eqd28GcPcqd98KYGYvmNmMYLnezH4WnFl9Jjjb9YKZvRNMfL3vLNrfux7AzC4wswXBWbFngi/dfWc87zOzV4H79r3ezMqAzwNfDc7g/puZbTCzhOB1mZ0fdzrOJ8xspZktM7OXgnVxZvbzYP1yM/tSsP7MIJ4VZnaXmSUF6zea2U/MbAnwCTM728zmmdkSM3vYzNL7/i0QERmQDlZ/bDSz/xd8hy8ys2lm9i8zW29mnw+2STezZ4Pv1xVmdlFPDxzUFy+a2d+CeujHZna5mS0M9jU22K7MzJ4Lvv+fNbOSbvY11sz+aWaLzexlM5sYrB9uZo8FdcoyMzu5awugmd1kZt/rZp/Tg/gWB+Ue2c0276sbD1D/dVsGC7fw3W5m84O/weygPlttZncf4O92gpm9FpRnoZllmFmymf0h+Lu9YWanB9teZWaPBn+bt83sp8H6HwMpQXz3B+v+GpR1lZnN6XS8c4L3d1kQe3fle1/d3Y2PA/8Mlr8I3LMvaQNw90fcfYeZ5QaxLA/+LscFcbynhTU4XllwW21mvw9if8rMUiycCM4gPLH9UjNLAV4GzrLwBNISa9xdN90G/Q1IB5YCa4H/BT7Q6bkXgBnBsgPnBsuPAU8BCcAUYGmwfjbw92D5KuC2YDmHdye1vw7472D5e8BiIKWb138PuKlTLH8APhIsz9m3jy5lWQGMCpazg/svAI8A8cHjXCAZqADGB+vuBW4IljcC3wiW84GXgLTg8TeBW6L9nummm266xcLtEPXHRuALwfIvgOWEW0QKgB3B+nggM1jOB9Z1qivqg/syYGU3x54N1BBOHpOALcD3g+e+AvwyWH4CuDJYvgb4a7C8v44BngXGBcuzgOeC5T93qhvigKyu8QA3Ad8Llu8GLiZcN74GFATrLwHu6qYMB6sbO9d/ByrD3cCDgAEXAXXAsYQbHxYDU7scLxF4BzgheJwZvAdf2xcfMBEoJ1xPXhVsnxU83gQUd35/Ou07N7hPIdxKlRe81xXA6C7bdC3f++ruLvseDSzu9PhR4KIDfCZ/DXw3WD6Dd3+fdD3myuC9LAPa9v2tgIeATwfLLxD8Bur0uqeB6dH+39Pt/Te1uMmQ4O71wHTCyVAl8Gczu6qbTVt492zXCuBFd28NlssOcZgi4F9mtgL4OnBMp+ced/e9PQj1DuDqYPlqwolcV68Cd5vZZwlXsgBnAb9z9zYAd68GJgAb3H1tsM09wGmd9vPn4P5EYBLwqpktBa4ESnsQq4jIoNeD+uPx4H4FsMDd97h7JdBsZtmEE44fmdly4BlgFDD8MEJ43d23ebjFbz3hE4r7jlcWLJ8E/ClYvg84tfMOLNyL4mTg4eB7/neEk0EI//C/PShru7vX9jCuCcBk4Olgn98hXA92dbC6sbODleEJD2cUKwgnxCvcvQNYxfvr5gnANnd/PShTXVA3ngr8MVj3FuEEbXzwmmfdvdbdm4A3OXAd+GUzWwbMB4qBcYTr0JfcfUOw7+oDvLa7uruzkYQ/Xz1xKuG/Ee7+HJBnZpmHeM0Gd18aLC/m4L9pdgKFB3leokTNoDJkePg6rheAF4IK5ErCZ/I6aw0qB4AOYF/XmI4edBv4NXCruz9uZrMJn/nap6GHMb4adGmYDcS5+/suVnf3z1v4wvgPA4vNbHpP9t2NfTEZ8LS7X9bL/YiIDGqHqD+ag/uOTsv7HscDlxNulZnu7q1mtpFwy05Pdd1n5+P19HdcCKhx96k93L6N915O0128Bqxy95MOsa+D1Y09dai/8ZHqvM/27vYZxH4WcJK7N5rZCxzG+9hd3e3uuzptsrfL/lYRPmHwt54eg4O/b13LmHKQ/SQH8UiMUYubDAlmNsHeO0rSVMJn2/pSFuFuLBCu1HtiD+FuNZ3dS/isY3etbZjZWHdf4O63ED47V0y4W8Pn9iWXZpYLrAHKzOyo4KVXAC92s8v5wCn7tjOzNDMb3812IiJDTh/UH1nAziBpO53I9Gh4Dbg0WL6c8HVK+7l7HbDBzD4BYGFTgqefJdzdft/10lnADmCYmeVZ+Nro87s55hqgwMKDt2BmCWbWXWvagerGrvXfQctwGNYAI83shCCujKBufDnYL0EdVxJsezCt9u515lnA7iBpm0i4pQ3CdehpZjY62Hdud+U7QN3d2Vre2wp2G3CldRrB1Mw+ZuHr5zuXZTbhazDrCHfdnRasn0a4++WhdPc7ZDzhbpYSY5S4yVCRDtxjZm8G3VUm0buzfgfzPcLdUBYDVT18zRPAR/ddvBysu5/wNQEPHOA1Pwsurl5JuKJbRriLZTmwPOjG8amgy8fVQUwrCJ+Z/G3XnQVdeq4CHgj+NvMI9/8XEZEjrz/uB2YE38OfAd7q+xD5EnB1EN8VhK9/6+py4NqgjlhF+Hoxgm1PD+JbDEwKLhH4AbCQ8InB98Xs7i2Er3X7SbDPpYS7Y3b1PbqvG7vWfz0pwyEFcV0C/DqI62nCLUj/C4SCcv4ZuCrofnowcwnXq/cTvowi3sxWAz8mnLDtq0PnAI8Gx9t3GULX8nVXd3eOuwFYv+8kqrvvIJzI/tzC0wGsBj5EONH6HjA9+Fv9mHcT4r8AuWa2CriecDJ4KHcDv903OEmQGO519+09eK30s30Xi4pIjAhGebrI3a+IdiwiIiLSP8zso4S71H4nijF8Fahz9zujFYMcmK5xE4khZvZr4FzgvGjHIiIiIv3H3R8zs7woh1FDMPCJxB61uImIiIiIiMQ4XeMmIiIiIiIS45S4iYiIiIiIxDglbiIiIiIiIjFOiZuIiIiIiEiMU+ImIiIiIiIS4/5/d+h8wOEh4hYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1080x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "if 'dssp_ratio' in df:\n",
    "    fig, axs = plt.subplots(1, 3, figsize=(15, 4))\n",
    "else: \n",
    "    fig, axs = plt.subplots(1, 2, figsize=(15, 4))\n",
    "\n",
    "plt.subplots_adjust(wspace=0.2)\n",
    "    \n",
    "g1=sns.histplot(df['similarity'], kde=True, ax = axs[0])\n",
    "g1.axvline(df['similarity'].median(), color='red')\n",
    "axs[0].set_xlabel('Similarity score')\n",
    "\n",
    "g2=sns.histplot(df['mol_contacts'], kde=True, binwidth=1, ax = axs[1])\n",
    "g2.axvline(df['mol_contacts'].median(), color='red')\n",
    "axs[1].set_xlabel('Small molecule atom contacts (Count)')\n",
    "\n",
    "if 'dssp_ratio' in df:\n",
    "    g3=sns.histplot(df['dssp_ratio'], kde=True, ax = axs[2])\n",
    "    g3.axvline(df['dssp_ratio'].median(), color='red')\n",
    "    axs[2].set_xlabel('Beta sheet contact (%)')\n",
    "    print(f\"Beta sheet contact percentage median: {df['dssp_ratio'].median():.2f}%\")\n",
    "    \n",
    "print(f\"Similarity median: {df['similarity'].median():.2f}\")\n",
    "print(f\"Small molecule contacts median: {df['mol_contacts'].median():.2f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Selection\n",
    "\n",
    "This part aims to select the best seeds based on the different metrics used. You can use the default recommended cutoffs (Usually the quartile) or using your own cutoffs.\n",
    "\n",
    "If two seeds are highly similar (Similarity score > 0.7), only the one with the best dSASA-normalized binding energy (norm. ddG) will be kept."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Setting the cutoffs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "default_cutoff={'ddg_post': df['ddg_post'].quantile(q=0.75), \n",
    "         'nddg_post' : df['nddg_post'].quantile(q=0.75),\n",
    "         'bunsh_post': df['bunsh_post'].quantile(q=0.75),\n",
    "         'bunsh2_post': df['bunsh2_post'].quantile(q=0.75), \n",
    "         'sc_post': df['sc_post'].quantile(q=0.25),\n",
    "         'hbonds_post': df['hbonds_post'].quantile(q=0.25),\n",
    "         'sasa_post' : df['sasa_post'].quantile(q=0.25),\n",
    "         'mol_contacts' : df['mol_contacts'].quantile(q=0.25),\n",
    "         'dssp_ratio' : 66}\n",
    "\n",
    "customed_cutoff={'ddg_post': -24, \n",
    "         'nddg_post': -23,\n",
    "         'bunsh_post': 1,\n",
    "         'bunsh2_post': 2, \n",
    "         'sc_post': 0.6,\n",
    "         'hbonds_post': 3,\n",
    "         'sasa_post' : 1000,\n",
    "         'mol_contacts' : 5,\n",
    "         'dssp_ratio' : 60}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Making a selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_selection(df, cutoff):\n",
    "    select=df[(df['ddg_post'] <= cutoff['ddg_post']) & \n",
    "          (df['nddg_post'] <= cutoff['nddg_post']) & \n",
    "          (df['bunsh_post'] <= cutoff['bunsh_post']) & \n",
    "          (df['bunsh2_post'] <= cutoff['bunsh2_post']) & \n",
    "          (df['sc_post'] >= cutoff['sc_post']) &\n",
    "          (df['hbonds_post'] >= cutoff['hbonds_post']) & \n",
    "          (df['sasa_post'] >= cutoff['sasa_post']) & \n",
    "          (df['mol_contacts'] >= cutoff['mol_contacts'])]\n",
    "    if 'dssp_ratio' in df:\n",
    "        select=select[select['dssp_ratio']>=cutoff['dssp_ratio']]\n",
    "    return select"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of seeds selected: 1\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\antho\\anaconda3\\lib\\site-packages\\pandas\\core\\frame.py:4305: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().drop(\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bunsh2_post</th>\n",
       "      <th>bunsh2_pre</th>\n",
       "      <th>bunsh_post</th>\n",
       "      <th>bunsh_pre</th>\n",
       "      <th>cms_post</th>\n",
       "      <th>cms_pre</th>\n",
       "      <th>ddg_post</th>\n",
       "      <th>ddg_pre</th>\n",
       "      <th>hbonds_post</th>\n",
       "      <th>hbonds_pre</th>\n",
       "      <th>...</th>\n",
       "      <th>sasa_pre</th>\n",
       "      <th>sc_post</th>\n",
       "      <th>sc_pre</th>\n",
       "      <th>description</th>\n",
       "      <th>seed</th>\n",
       "      <th>nddg_pre</th>\n",
       "      <th>nddg_post</th>\n",
       "      <th>similarity</th>\n",
       "      <th>closest_neighboor</th>\n",
       "      <th>mol_contacts</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>188.816</td>\n",
       "      <td>179.679</td>\n",
       "      <td>-22.69</td>\n",
       "      <td>-18.959</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1050.463</td>\n",
       "      <td>0.763</td>\n",
       "      <td>0.783</td>\n",
       "      <td>6O0K_A_102225-3r6f_A_9</td>\n",
       "      <td>102225-3r6f_A_9</td>\n",
       "      <td>-18.048232</td>\n",
       "      <td>-20.449234</td>\n",
       "      <td>0.8</td>\n",
       "      <td>6O0K_A_102225-3r6f_A_3</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   bunsh2_post  bunsh2_pre  bunsh_post  bunsh_pre  cms_post  cms_pre  \\\n",
       "5          6.0         7.0         3.0        4.0   188.816  179.679   \n",
       "\n",
       "   ddg_post  ddg_pre  hbonds_post  hbonds_pre  ...  sasa_pre  sc_post  sc_pre  \\\n",
       "5    -22.69  -18.959          4.0         3.0  ...  1050.463    0.763   0.783   \n",
       "\n",
       "              description             seed   nddg_pre  nddg_post  similarity  \\\n",
       "5  6O0K_A_102225-3r6f_A_9  102225-3r6f_A_9 -18.048232 -20.449234         0.8   \n",
       "\n",
       "        closest_neighboor mol_contacts  \n",
       "5  6O0K_A_102225-3r6f_A_3           11  \n",
       "\n",
       "[1 rows x 21 columns]"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "select = make_selection(df, default_cutoff)\n",
    "#select = make_selection(df, customed_cutoff)\n",
    "\n",
    "to_drop=[]\n",
    "for idx in select.index:\n",
    "    if select.at[idx,'similarity'] > 0.7:\n",
    "        closest=select.at[idx,'closest_neighboor']\n",
    "        if select['description'].str.contains(closest).any():\n",
    "            if (len(select.index[select['description'] == closest].to_list())!=0):\n",
    "                idx2=select.index[select['description'] == closest].to_list()[0]\n",
    "            ddg1=select.at[idx,'nddg_post']\n",
    "            ddg2=select.at[idx2,'nddg_post']\n",
    "            if ddg1<=ddg2:\n",
    "                to_drop.append(idx2)\n",
    "            else:\n",
    "                to_drop.append(idx)\n",
    "\n",
    "select.drop(index=to_drop, inplace=True)                \n",
    "\n",
    "print(r\"Number of seeds selected: {}\".format(select.shape[0]))\n",
    "select.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Copying the selected files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cp ./out/6O0K_A_102225-3r6f_A_9.pdb ./selected\n"
     ]
    }
   ],
   "source": [
    "cmd = r\"cp \"+ ''.join('./out/' + select['description'] + \".pdb \") + './selected'\n",
    "output = sp.run(cmd, shell=True, capture_output=True, text=True)\n",
    "print(cmd)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
